id	sid	tid	token	lemma	pos
ijassa-1239	1	1	adv	adv	PROPN
ijassa-1239	1	2	syst	syst	PROPN
ijassa-1239	1	3	sci	sci	PROPN
ijassa-1239	1	4	appl	appl	PROPN
ijassa-1239	1	5	2022	2022	NUM
ijassa-1239	1	6	;	;	PUNCT
ijassa-1239	1	7	03:70–83	03:70–83	NUM
ijassa-1239	1	8	published	publish	VERB
ijassa-1239	1	9	online	online	ADV
ijassa-1239	1	10	at	at	ADP
ijassa-1239	1	11	https://ijassa.ipu.ru	https://ijassa.ipu.ru	ADV
ijassa-1239	1	12	.	.	PUNCT
ijassa-1239	2	1	the	the	DET
ijassa-1239	2	2	analysis	analysis	NOUN
ijassa-1239	2	3	of	of	ADP
ijassa-1239	2	4	big	big	ADJ
ijassa-1239	2	5	data	datum	NOUN
ijassa-1239	2	6	centers	center	NOUN
ijassa-1239	2	7	performance	performance	NOUN
ijassa-1239	2	8	anastasia	anastasia	PROPN
ijassa-1239	2	9	v.	v.	PROPN
ijassa-1239	2	10	gorbunova1	gorbunova1	PROPN
ijassa-1239	2	11	*	*	PROPN
ijassa-1239	2	12	,	,	PUNCT
ijassa-1239	2	13	vladimir	vladimir	PROPN
ijassa-1239	2	14	m.	m.	PROPN
ijassa-1239	2	15	vishnevsky1	vishnevsky1	PROPN
ijassa-1239	3	1	1v.a	1v.a	NUM
ijassa-1239	3	2	.	.	PUNCT
ijassa-1239	3	3	trapeznikov	trapeznikov	PROPN
ijassa-1239	3	4	institute	institute	PROPN
ijassa-1239	3	5	of	of	ADP
ijassa-1239	3	6	control	control	PROPN
ijassa-1239	3	7	sciences	sciences	PROPN
ijassa-1239	3	8	of	of	ADP
ijassa-1239	3	9	russian	russian	ADJ
ijassa-1239	3	10	academy	academy	PROPN
ijassa-1239	3	11	of	of	ADP
ijassa-1239	3	12	sciences	sciences	PROPN
ijassa-1239	3	13	,	,	PUNCT
ijassa-1239	3	14	moscow	moscow	PROPN
ijassa-1239	3	15	,	,	PUNCT
ijassa-1239	3	16	russia	russia	PROPN
ijassa-1239	3	17	abstract	abstract	NOUN
ijassa-1239	3	18	:	:	PUNCT
ijassa-1239	3	19	the	the	DET
ijassa-1239	3	20	article	article	NOUN
ijassa-1239	3	21	proposes	propose	VERB
ijassa-1239	3	22	the	the	DET
ijassa-1239	3	23	approach	approach	NOUN
ijassa-1239	3	24	for	for	ADP
ijassa-1239	3	25	predicting	predict	VERB
ijassa-1239	3	26	the	the	DET
ijassa-1239	3	27	performance	performance	NOUN
ijassa-1239	3	28	of	of	ADP
ijassa-1239	3	29	big	big	ADJ
ijassa-1239	3	30	data	datum	NOUN
ijassa-1239	3	31	processing	processing	NOUN
ijassa-1239	3	32	center	center	NOUN
ijassa-1239	3	33	services	service	NOUN
ijassa-1239	3	34	.	.	PUNCT
ijassa-1239	4	1	to	to	PART
ijassa-1239	4	2	simulate	simulate	VERB
ijassa-1239	4	3	the	the	DET
ijassa-1239	4	4	process	process	NOUN
ijassa-1239	4	5	of	of	ADP
ijassa-1239	4	6	parallel	parallel	ADJ
ijassa-1239	4	7	computing	computing	NOUN
ijassa-1239	4	8	,	,	PUNCT
ijassa-1239	4	9	the	the	DET
ijassa-1239	4	10	fork	fork	NOUN
ijassa-1239	4	11	-	-	PUNCT
ijassa-1239	4	12	join	join	NOUN
ijassa-1239	4	13	queuing	queuing	NOUN
ijassa-1239	4	14	system	system	NOUN
ijassa-1239	4	15	(	(	PUNCT
ijassa-1239	4	16	qs	qs	NOUN
ijassa-1239	4	17	)	)	PUNCT
ijassa-1239	4	18	with	with	ADP
ijassa-1239	4	19	a	a	DET
ijassa-1239	4	20	truncated	truncated	ADJ
ijassa-1239	4	21	pareto	pareto	ADJ
ijassa-1239	4	22	distribution	distribution	NOUN
ijassa-1239	4	23	of	of	ADP
ijassa-1239	4	24	service	service	NOUN
ijassa-1239	4	25	time	time	NOUN
ijassa-1239	4	26	and	and	CCONJ
ijassa-1239	4	27	three	three	NUM
ijassa-1239	4	28	variants	variant	NOUN
ijassa-1239	4	29	of	of	ADP
ijassa-1239	4	30	distributions	distribution	NOUN
ijassa-1239	4	31	for	for	ADP
ijassa-1239	4	32	the	the	DET
ijassa-1239	4	33	incoming	incoming	ADJ
ijassa-1239	4	34	flow	flow	NOUN
ijassa-1239	4	35	is	be	AUX
ijassa-1239	4	36	used	use	VERB
ijassa-1239	4	37	.	.	PUNCT
ijassa-1239	5	1	the	the	DET
ijassa-1239	5	2	number	number	NOUN
ijassa-1239	5	3	of	of	ADP
ijassa-1239	5	4	devices	device	NOUN
ijassa-1239	5	5	in	in	ADP
ijassa-1239	5	6	each	each	PRON
ijassa-1239	5	7	of	of	ADP
ijassa-1239	5	8	the	the	DET
ijassa-1239	5	9	fork	fork	NOUN
ijassa-1239	5	10	-	-	PUNCT
ijassa-1239	5	11	join	join	NOUN
ijassa-1239	5	12	subsystems	subsystem	NOUN
ijassa-1239	5	13	of	of	ADP
ijassa-1239	5	14	the	the	DET
ijassa-1239	5	15	qs	qs	NOUN
ijassa-1239	5	16	can	can	AUX
ijassa-1239	5	17	be	be	AUX
ijassa-1239	5	18	more	more	ADJ
ijassa-1239	5	19	than	than	ADP
ijassa-1239	5	20	one	one	NUM
ijassa-1239	5	21	.	.	PUNCT
ijassa-1239	6	1	the	the	DET
ijassa-1239	6	2	performance	performance	NOUN
ijassa-1239	6	3	scores	score	NOUN
ijassa-1239	6	4	are	be	AUX
ijassa-1239	6	5	the	the	DET
ijassa-1239	6	6	average	average	ADJ
ijassa-1239	6	7	system	system	NOUN
ijassa-1239	6	8	response	response	NOUN
ijassa-1239	6	9	time	time	NOUN
ijassa-1239	6	10	and	and	CCONJ
ijassa-1239	6	11	its	its	PRON
ijassa-1239	6	12	tail	tail	NOUN
ijassa-1239	6	13	delay	delay	NOUN
ijassa-1239	6	14	(	(	PUNCT
ijassa-1239	6	15	99th	99th	ADJ
ijassa-1239	6	16	percentile	percentile	NOUN
ijassa-1239	6	17	of	of	ADP
ijassa-1239	6	18	the	the	DET
ijassa-1239	6	19	response	response	NOUN
ijassa-1239	6	20	time	time	NOUN
ijassa-1239	6	21	distribution	distribution	NOUN
ijassa-1239	6	22	)	)	PUNCT
ijassa-1239	6	23	.	.	PUNCT
ijassa-1239	7	1	the	the	DET
ijassa-1239	7	2	approach	approach	NOUN
ijassa-1239	7	3	is	be	AUX
ijassa-1239	7	4	based	base	VERB
ijassa-1239	7	5	on	on	ADP
ijassa-1239	7	6	a	a	DET
ijassa-1239	7	7	combination	combination	NOUN
ijassa-1239	7	8	of	of	ADP
ijassa-1239	7	9	simulation	simulation	NOUN
ijassa-1239	7	10	modeling	modeling	NOUN
ijassa-1239	7	11	and	and	CCONJ
ijassa-1239	7	12	neural	neural	ADJ
ijassa-1239	7	13	networks	network	NOUN
ijassa-1239	7	14	,	,	PUNCT
ijassa-1239	7	15	as	as	ADP
ijassa-1239	7	16	one	one	NUM
ijassa-1239	7	17	of	of	ADP
ijassa-1239	7	18	the	the	DET
ijassa-1239	7	19	methods	method	NOUN
ijassa-1239	7	20	of	of	ADP
ijassa-1239	7	21	machine	machine	NOUN
ijassa-1239	7	22	learning	learning	NOUN
ijassa-1239	7	23	.	.	PUNCT
ijassa-1239	8	1	for	for	ADP
ijassa-1239	8	2	at	at	ADV
ijassa-1239	8	3	least	least	ADV
ijassa-1239	8	4	93	93	NUM
ijassa-1239	8	5	%	%	NOUN
ijassa-1239	8	6	of	of	ADP
ijassa-1239	8	7	the	the	DET
ijassa-1239	8	8	data	datum	NOUN
ijassa-1239	8	9	used	use	VERB
ijassa-1239	8	10	to	to	PART
ijassa-1239	8	11	test	test	VERB
ijassa-1239	8	12	the	the	DET
ijassa-1239	8	13	proposed	propose	VERB
ijassa-1239	8	14	method	method	NOUN
ijassa-1239	8	15	in	in	ADP
ijassa-1239	8	16	the	the	DET
ijassa-1239	8	17	course	course	NOUN
ijassa-1239	8	18	of	of	ADP
ijassa-1239	8	19	a	a	DET
ijassa-1239	8	20	numerical	numerical	ADJ
ijassa-1239	8	21	experiment	experiment	NOUN
ijassa-1239	8	22	the	the	DET
ijassa-1239	8	23	approximation	approximation	NOUN
ijassa-1239	8	24	error	error	NOUN
ijassa-1239	8	25	of	of	ADP
ijassa-1239	8	26	both	both	DET
ijassa-1239	8	27	studied	study	VERB
ijassa-1239	8	28	characteristics	characteristic	NOUN
ijassa-1239	8	29	does	do	AUX
ijassa-1239	8	30	not	not	PART
ijassa-1239	8	31	exceed	exceed	VERB
ijassa-1239	8	32	5	5	NUM
ijassa-1239	8	33	%	%	NOUN
ijassa-1239	8	34	,	,	PUNCT
ijassa-1239	8	35	while	while	SCONJ
ijassa-1239	8	36	the	the	DET
ijassa-1239	8	37	maximum	maximum	ADJ
ijassa-1239	8	38	approximation	approximation	NOUN
ijassa-1239	8	39	error	error	NOUN
ijassa-1239	8	40	is	be	AUX
ijassa-1239	8	41	not	not	PART
ijassa-1239	8	42	more	more	ADJ
ijassa-1239	8	43	than	than	ADP
ijassa-1239	8	44	10	10	NUM
ijassa-1239	8	45	%	%	NOUN
ijassa-1239	8	46	.	.	PUNCT
ijassa-1239	9	1	keywords	keyword	NOUN
ijassa-1239	9	2	:	:	PUNCT
ijassa-1239	9	3	parallel	parallel	ADJ
ijassa-1239	9	4	computing	computing	NOUN
ijassa-1239	9	5	,	,	PUNCT
ijassa-1239	9	6	data	datum	NOUN
ijassa-1239	9	7	-	-	PUNCT
ijassa-1239	9	8	intensive	intensive	ADJ
ijassa-1239	9	9	applications	application	NOUN
ijassa-1239	9	10	,	,	PUNCT
ijassa-1239	9	11	big	big	ADJ
ijassa-1239	9	12	data	datum	NOUN
ijassa-1239	9	13	,	,	PUNCT
ijassa-1239	9	14	fork	fork	NOUN
ijassa-1239	9	15	-	-	PUNCT
ijassa-1239	9	16	join	join	NOUN
ijassa-1239	9	17	queueing	queue	VERB
ijassa-1239	9	18	system	system	NOUN
ijassa-1239	9	19	,	,	PUNCT
ijassa-1239	9	20	average	average	ADJ
ijassa-1239	9	21	response	response	NOUN
ijassa-1239	9	22	time	time	NOUN
ijassa-1239	9	23	,	,	PUNCT
ijassa-1239	9	24	artificial	artificial	ADJ
ijassa-1239	9	25	neural	neural	ADJ
ijassa-1239	9	26	networks	network	NOUN
ijassa-1239	9	27	,	,	PUNCT
ijassa-1239	9	28	machine	machine	NOUN
ijassa-1239	9	29	learning	learning	NOUN
ijassa-1239	9	30	methods	method	NOUN
ijassa-1239	9	31	1	1	NUM
ijassa-1239	9	32	.	.	PUNCT
ijassa-1239	10	1	introduction	introduction	NOUN
ijassa-1239	10	2	according	accord	VERB
ijassa-1239	10	3	to	to	ADP
ijassa-1239	10	4	an	an	DET
ijassa-1239	10	5	idc	idc	PROPN
ijassa-1239	10	6	(	(	PUNCT
ijassa-1239	10	7	international	international	ADJ
ijassa-1239	10	8	data	data	NOUN
ijassa-1239	10	9	corporation	corporation	NOUN
ijassa-1239	10	10	)	)	PUNCT
ijassa-1239	10	11	report	report	NOUN
ijassa-1239	10	12	[	[	X
ijassa-1239	10	13	19	19	NUM
ijassa-1239	10	14	]	]	PUNCT
ijassa-1239	10	15	,	,	PUNCT
ijassa-1239	10	16	digital	digital	ADJ
ijassa-1239	10	17	data	datum	NOUN
ijassa-1239	10	18	continues	continue	VERB
ijassa-1239	10	19	to	to	PART
ijassa-1239	10	20	grow	grow	VERB
ijassa-1239	10	21	relentlessly	relentlessly	ADV
ijassa-1239	10	22	.	.	PUNCT
ijassa-1239	11	1	thus	thus	ADV
ijassa-1239	11	2	,	,	PUNCT
ijassa-1239	11	3	according	accord	VERB
ijassa-1239	11	4	to	to	ADP
ijassa-1239	11	5	forecasts	forecast	NOUN
ijassa-1239	11	6	,	,	PUNCT
ijassa-1239	11	7	by	by	ADP
ijassa-1239	11	8	2025	2025	NUM
ijassa-1239	11	9	the	the	DET
ijassa-1239	11	10	global	global	ADJ
ijassa-1239	11	11	datasphere	datasphere	NOUN
ijassa-1239	11	12	will	will	AUX
ijassa-1239	11	13	increase	increase	VERB
ijassa-1239	11	14	to	to	ADP
ijassa-1239	11	15	175	175	NUM
ijassa-1239	11	16	zettabytes	zettabyte	NOUN
ijassa-1239	11	17	[	[	X
ijassa-1239	11	18	19	19	NUM
ijassa-1239	11	19	]	]	PUNCT
ijassa-1239	11	20	.	.	PUNCT
ijassa-1239	12	1	this	this	PRON
ijassa-1239	12	2	is	be	AUX
ijassa-1239	12	3	more	more	ADJ
ijassa-1239	12	4	than	than	ADP
ijassa-1239	12	5	five	five	NUM
ijassa-1239	12	6	times	time	NOUN
ijassa-1239	12	7	the	the	DET
ijassa-1239	12	8	amount	amount	NOUN
ijassa-1239	12	9	of	of	ADP
ijassa-1239	12	10	digital	digital	ADJ
ijassa-1239	12	11	data	datum	NOUN
ijassa-1239	12	12	available	available	ADJ
ijassa-1239	12	13	as	as	ADP
ijassa-1239	12	14	of	of	ADP
ijassa-1239	12	15	2018	2018	NUM
ijassa-1239	12	16	.	.	PUNCT
ijassa-1239	13	1	in	in	ADP
ijassa-1239	13	2	the	the	DET
ijassa-1239	13	3	field	field	NOUN
ijassa-1239	13	4	of	of	ADP
ijassa-1239	13	5	scientific	scientific	ADJ
ijassa-1239	13	6	research	research	NOUN
ijassa-1239	13	7	,	,	PUNCT
ijassa-1239	13	8	this	this	DET
ijassa-1239	13	9	trend	trend	NOUN
ijassa-1239	13	10	has	have	AUX
ijassa-1239	13	11	led	lead	VERB
ijassa-1239	13	12	to	to	ADP
ijassa-1239	13	13	the	the	DET
ijassa-1239	13	14	formation	formation	NOUN
ijassa-1239	13	15	of	of	ADP
ijassa-1239	13	16	the	the	DET
ijassa-1239	13	17	so	so	ADV
ijassa-1239	13	18	-	-	PUNCT
ijassa-1239	13	19	called	call	VERB
ijassa-1239	13	20	“	"	PUNCT
ijassa-1239	13	21	fourth	fourth	ADJ
ijassa-1239	13	22	paradigm	paradigm	NOUN
ijassa-1239	13	23	”	"	PUNCT
ijassa-1239	13	24	,	,	PUNCT
ijassa-1239	13	25	along	along	ADP
ijassa-1239	13	26	with	with	ADP
ijassa-1239	13	27	experimental	experimental	ADJ
ijassa-1239	13	28	,	,	PUNCT
ijassa-1239	13	29	theoretical	theoretical	ADJ
ijassa-1239	13	30	and	and	CCONJ
ijassa-1239	13	31	computational	computational	ADJ
ijassa-1239	13	32	ones	one	NOUN
ijassa-1239	13	33	.	.	PUNCT
ijassa-1239	14	1	its	its	PRON
ijassa-1239	14	2	feature	feature	NOUN
ijassa-1239	14	3	is	be	AUX
ijassa-1239	14	4	the	the	DET
ijassa-1239	14	5	use	use	NOUN
ijassa-1239	14	6	of	of	ADP
ijassa-1239	14	7	big	big	ADJ
ijassa-1239	14	8	data	datum	NOUN
ijassa-1239	14	9	technologies	technology	NOUN
ijassa-1239	14	10	.	.	PUNCT
ijassa-1239	15	1	at	at	ADP
ijassa-1239	15	2	the	the	DET
ijassa-1239	15	3	same	same	ADJ
ijassa-1239	15	4	time	time	NOUN
ijassa-1239	15	5	,	,	PUNCT
ijassa-1239	15	6	science	science	NOUN
ijassa-1239	15	7	that	that	PRON
ijassa-1239	15	8	uses	use	VERB
ijassa-1239	15	9	big	big	ADJ
ijassa-1239	15	10	data	datum	NOUN
ijassa-1239	15	11	is	be	AUX
ijassa-1239	15	12	also	also	ADV
ijassa-1239	15	13	characterized	characterize	VERB
ijassa-1239	15	14	by	by	ADP
ijassa-1239	15	15	interdisciplinarity	interdisciplinarity	NOUN
ijassa-1239	15	16	,	,	PUNCT
ijassa-1239	15	17	i.e.	i.e.	X
ijassa-1239	15	18	,	,	PUNCT
ijassa-1239	15	19	it	it	PRON
ijassa-1239	15	20	combines	combine	VERB
ijassa-1239	15	21	modeling	modeling	NOUN
ijassa-1239	15	22	,	,	PUNCT
ijassa-1239	15	23	theory	theory	NOUN
ijassa-1239	15	24	and	and	CCONJ
ijassa-1239	15	25	experiment	experiment	NOUN
ijassa-1239	15	26	.	.	PUNCT
ijassa-1239	16	1	working	work	VERB
ijassa-1239	16	2	with	with	ADP
ijassa-1239	16	3	big	big	ADJ
ijassa-1239	16	4	data	datum	NOUN
ijassa-1239	16	5	for	for	ADP
ijassa-1239	16	6	both	both	CCONJ
ijassa-1239	16	7	scientific	scientific	ADJ
ijassa-1239	16	8	and	and	CCONJ
ijassa-1239	16	9	engineering	engineering	NOUN
ijassa-1239	16	10	calculations	calculation	NOUN
ijassa-1239	16	11	has	have	AUX
ijassa-1239	16	12	become	become	VERB
ijassa-1239	16	13	available	available	ADJ
ijassa-1239	16	14	mainly	mainly	ADV
ijassa-1239	16	15	due	due	ADP
ijassa-1239	16	16	to	to	ADP
ijassa-1239	16	17	the	the	DET
ijassa-1239	16	18	development	development	NOUN
ijassa-1239	16	19	of	of	ADP
ijassa-1239	16	20	cloud	cloud	NOUN
ijassa-1239	16	21	technologies	technology	NOUN
ijassa-1239	16	22	,	,	PUNCT
ijassa-1239	16	23	as	as	ADV
ijassa-1239	16	24	well	well	ADV
ijassa-1239	16	25	as	as	ADP
ijassa-1239	16	26	the	the	DET
ijassa-1239	16	27	emergence	emergence	NOUN
ijassa-1239	16	28	of	of	ADP
ijassa-1239	16	29	many	many	ADJ
ijassa-1239	16	30	scientific	scientific	ADJ
ijassa-1239	16	31	and	and	CCONJ
ijassa-1239	16	32	technical	technical	ADJ
ijassa-1239	16	33	applications	application	NOUN
ijassa-1239	16	34	that	that	PRON
ijassa-1239	16	35	use	use	VERB
ijassa-1239	16	36	the	the	DET
ijassa-1239	16	37	services	service	NOUN
ijassa-1239	16	38	of	of	ADP
ijassa-1239	16	39	cloud	cloud	NOUN
ijassa-1239	16	40	providers	provider	NOUN
ijassa-1239	16	41	for	for	ADP
ijassa-1239	16	42	computing	computing	NOUN
ijassa-1239	16	43	and	and	CCONJ
ijassa-1239	16	44	data	datum	NOUN
ijassa-1239	16	45	processing	processing	NOUN
ijassa-1239	16	46	[	[	X
ijassa-1239	16	47	17	17	NUM
ijassa-1239	16	48	]	]	PUNCT
ijassa-1239	16	49	.	.	PUNCT
ijassa-1239	17	1	at	at	ADP
ijassa-1239	17	2	the	the	DET
ijassa-1239	17	3	same	same	ADJ
ijassa-1239	17	4	time	time	NOUN
ijassa-1239	17	5	,	,	PUNCT
ijassa-1239	17	6	the	the	DET
ijassa-1239	17	7	issue	issue	NOUN
ijassa-1239	17	8	of	of	ADP
ijassa-1239	17	9	improving	improve	VERB
ijassa-1239	17	10	application	application	NOUN
ijassa-1239	17	11	performance	performance	NOUN
ijassa-1239	17	12	comes	come	VERB
ijassa-1239	17	13	to	to	PART
ijassa-1239	17	14	be	be	AUX
ijassa-1239	17	15	in	in	ADP
ijassa-1239	17	16	the	the	DET
ijassa-1239	17	17	foreground	foreground	NOUN
ijassa-1239	17	18	.	.	PUNCT
ijassa-1239	18	1	one	one	NUM
ijassa-1239	18	2	of	of	ADP
ijassa-1239	18	3	the	the	DET
ijassa-1239	18	4	main	main	ADJ
ijassa-1239	18	5	ways	way	NOUN
ijassa-1239	18	6	to	to	PART
ijassa-1239	18	7	improve	improve	VERB
ijassa-1239	18	8	the	the	DET
ijassa-1239	18	9	performance	performance	NOUN
ijassa-1239	18	10	of	of	ADP
ijassa-1239	18	11	various	various	ADJ
ijassa-1239	18	12	kinds	kind	NOUN
ijassa-1239	18	13	of	of	ADP
ijassa-1239	18	14	data	datum	NOUN
ijassa-1239	18	15	center	center	NOUN
ijassa-1239	18	16	services	service	NOUN
ijassa-1239	18	17	is	be	AUX
ijassa-1239	18	18	to	to	PART
ijassa-1239	18	19	parallelize	parallelize	VERB
ijassa-1239	18	20	calculations	calculation	NOUN
ijassa-1239	18	21	,	,	PUNCT
ijassa-1239	18	22	which	which	PRON
ijassa-1239	18	23	can	can	AUX
ijassa-1239	18	24	occur	occur	VERB
ijassa-1239	18	25	both	both	PRON
ijassa-1239	18	26	at	at	ADP
ijassa-1239	18	27	the	the	DET
ijassa-1239	18	28	hardware	hardware	NOUN
ijassa-1239	18	29	and	and	CCONJ
ijassa-1239	18	30	software	software	NOUN
ijassa-1239	18	31	levels	level	NOUN
ijassa-1239	18	32	[	[	X
ijassa-1239	18	33	17	17	NUM
ijassa-1239	18	34	]	]	PUNCT
ijassa-1239	18	35	.	.	PUNCT
ijassa-1239	19	1	the	the	DET
ijassa-1239	19	2	distribution	distribution	NOUN
ijassa-1239	19	3	of	of	ADP
ijassa-1239	19	4	workloads	workload	NOUN
ijassa-1239	19	5	can	can	AUX
ijassa-1239	19	6	be	be	AUX
ijassa-1239	19	7	based	base	VERB
ijassa-1239	19	8	on	on	ADP
ijassa-1239	19	9	the	the	DET
ijassa-1239	19	10	parallelization	parallelization	NOUN
ijassa-1239	19	11	of	of	ADP
ijassa-1239	19	12	the	the	DET
ijassa-1239	19	13	data	datum	NOUN
ijassa-1239	19	14	or	or	CCONJ
ijassa-1239	19	15	tasks	task	NOUN
ijassa-1239	19	16	themselves	themselves	PRON
ijassa-1239	19	17	.	.	PUNCT
ijassa-1239	20	1	by	by	ADP
ijassa-1239	20	2	now	now	ADV
ijassa-1239	20	3	,	,	PUNCT
ijassa-1239	20	4	many	many	ADJ
ijassa-1239	20	5	frameworks	framework	NOUN
ijassa-1239	20	6	have	have	AUX
ijassa-1239	20	7	been	be	AUX
ijassa-1239	20	8	developed	develop	VERB
ijassa-1239	20	9	with	with	ADP
ijassa-1239	20	10	a	a	DET
ijassa-1239	20	11	parallel	parallel	ADJ
ijassa-1239	20	12	approach	approach	NOUN
ijassa-1239	20	13	to	to	PART
ijassa-1239	20	14	speed	speed	VERB
ijassa-1239	20	15	up	up	ADP
ijassa-1239	20	16	data	datum	NOUN
ijassa-1239	20	17	-	-	PUNCT
ijassa-1239	20	18	intensive	intensive	ADJ
ijassa-1239	20	19	applications	application	NOUN
ijassa-1239	20	20	.	.	PUNCT
ijassa-1239	21	1	these	these	PRON
ijassa-1239	21	2	include	include	VERB
ijassa-1239	21	3	,	,	PUNCT
ijassa-1239	21	4	for	for	ADP
ijassa-1239	21	5	example	example	NOUN
ijassa-1239	21	6	,	,	PUNCT
ijassa-1239	21	7	the	the	DET
ijassa-1239	21	8	google	google	PROPN
ijassa-1239	21	9	mapreduce	mapreduce	PROPN
ijassa-1239	21	10	[	[	X
ijassa-1239	21	11	7	7	NUM
ijassa-1239	21	12	]	]	ADJ
ijassa-1239	21	13	framework	framework	NOUN
ijassa-1239	21	14	,	,	PUNCT
ijassa-1239	21	15	hadoop	hadoop	NOUN
ijassa-1239	21	16	mapreduce	mapreduce	NOUN
ijassa-1239	21	17	[	[	X
ijassa-1239	21	18	2	2	NUM
ijassa-1239	21	19	]	]	PUNCT
ijassa-1239	21	20	,	,	PUNCT
ijassa-1239	21	21	apache	apache	NOUN
ijassa-1239	21	22	spark	spark	NOUN
ijassa-1239	21	23	[	[	X
ijassa-1239	21	24	3	3	NUM
ijassa-1239	21	25	]	]	PUNCT
ijassa-1239	21	26	and	and	CCONJ
ijassa-1239	21	27	many	many	ADJ
ijassa-1239	21	28	others	other	NOUN
ijassa-1239	21	29	[	[	X
ijassa-1239	21	30	11	11	NUM
ijassa-1239	21	31	]	]	PUNCT
ijassa-1239	21	32	.	.	PUNCT
ijassa-1239	22	1	in	in	ADP
ijassa-1239	22	2	addition	addition	NOUN
ijassa-1239	22	3	to	to	ADP
ijassa-1239	22	4	addressing	address	VERB
ijassa-1239	22	5	development	development	NOUN
ijassa-1239	22	6	-	-	PUNCT
ijassa-1239	22	7	level	level	NOUN
ijassa-1239	22	8	performance	performance	NOUN
ijassa-1239	22	9	and	and	CCONJ
ijassa-1239	22	10	support	support	NOUN
ijassa-1239	22	11	environments	environment	NOUN
ijassa-1239	22	12	for	for	ADP
ijassa-1239	22	13	data	data	NOUN
ijassa-1239	22	14	-	-	PUNCT
ijassa-1239	22	15	intensive	intensive	ADJ
ijassa-1239	22	16	applications	application	NOUN
ijassa-1239	22	17	,	,	PUNCT
ijassa-1239	22	18	there	there	PRON
ijassa-1239	22	19	is	be	VERB
ijassa-1239	22	20	a	a	DET
ijassa-1239	22	21	natural	natural	ADJ
ijassa-1239	22	22	challenge	challenge	NOUN
ijassa-1239	22	23	in	in	ADP
ijassa-1239	22	24	practice	practice	NOUN
ijassa-1239	22	25	to	to	PART
ijassa-1239	22	26	optimally	optimally	ADV
ijassa-1239	22	27	allocate	allocate	VERB
ijassa-1239	22	28	∗corresponding	∗corresponde	VERB
ijassa-1239	22	29	author	author	NOUN
ijassa-1239	22	30	:	:	PUNCT
ijassa-1239	22	31	avgorbunova@list.ru	avgorbunova@list.ru	VERB
ijassa-1239	22	32	the	the	DET
ijassa-1239	22	33	analysis	analysis	NOUN
ijassa-1239	22	34	of	of	ADP
ijassa-1239	22	35	big	big	ADJ
ijassa-1239	22	36	data	datum	NOUN
ijassa-1239	22	37	centers	center	NOUN
ijassa-1239	22	38	performance	performance	VERB
ijassa-1239	22	39	71	71	NUM
ijassa-1239	22	40	data	datum	NOUN
ijassa-1239	22	41	center	center	NOUN
ijassa-1239	22	42	resources	resource	NOUN
ijassa-1239	22	43	while	while	SCONJ
ijassa-1239	22	44	meeting	meet	VERB
ijassa-1239	22	45	quality	quality	NOUN
ijassa-1239	22	46	-	-	PUNCT
ijassa-1239	22	47	of	of	ADP
ijassa-1239	22	48	-	-	PUNCT
ijassa-1239	22	49	service	service	NOUN
ijassa-1239	22	50	agreements	agreement	NOUN
ijassa-1239	22	51	.	.	PUNCT
ijassa-1239	23	1	due	due	ADP
ijassa-1239	23	2	to	to	ADP
ijassa-1239	23	3	the	the	DET
ijassa-1239	23	4	lack	lack	NOUN
ijassa-1239	23	5	of	of	ADP
ijassa-1239	23	6	good	good	ADJ
ijassa-1239	23	7	tools	tool	NOUN
ijassa-1239	23	8	to	to	PART
ijassa-1239	23	9	objectively	objectively	ADV
ijassa-1239	23	10	assess	assess	VERB
ijassa-1239	23	11	their	their	PRON
ijassa-1239	23	12	performance	performance	NOUN
ijassa-1239	23	13	characteristics	characteristic	NOUN
ijassa-1239	23	14	,	,	PUNCT
ijassa-1239	23	15	the	the	DET
ijassa-1239	23	16	main	main	ADJ
ijassa-1239	23	17	strategy	strategy	NOUN
ijassa-1239	23	18	at	at	ADP
ijassa-1239	23	19	present	present	NOUN
ijassa-1239	23	20	is	be	AUX
ijassa-1239	23	21	to	to	ADP
ijassa-1239	23	22	overprovision	overprovision	NOUN
ijassa-1239	23	23	resources	resource	NOUN
ijassa-1239	23	24	,	,	PUNCT
ijassa-1239	23	25	half	half	NOUN
ijassa-1239	23	26	of	of	ADP
ijassa-1239	23	27	which	which	PRON
ijassa-1239	23	28	are	be	AUX
ijassa-1239	23	29	idle	idle	ADJ
ijassa-1239	23	30	most	most	ADJ
ijassa-1239	23	31	of	of	ADP
ijassa-1239	23	32	the	the	DET
ijassa-1239	23	33	time	time	NOUN
ijassa-1239	23	34	[	[	X
ijassa-1239	23	35	1	1	NUM
ijassa-1239	23	36	,	,	PUNCT
ijassa-1239	23	37	5	5	NUM
ijassa-1239	23	38	]	]	PUNCT
ijassa-1239	23	39	.	.	PUNCT
ijassa-1239	24	1	this	this	PRON
ijassa-1239	24	2	leads	lead	VERB
ijassa-1239	24	3	to	to	ADP
ijassa-1239	24	4	a	a	DET
ijassa-1239	24	5	significant	significant	ADJ
ijassa-1239	24	6	increase	increase	NOUN
ijassa-1239	24	7	in	in	ADP
ijassa-1239	24	8	the	the	DET
ijassa-1239	24	9	cost	cost	NOUN
ijassa-1239	24	10	of	of	ADP
ijassa-1239	24	11	maintaining	maintain	VERB
ijassa-1239	24	12	equipment	equipment	NOUN
ijassa-1239	24	13	(	(	PUNCT
ijassa-1239	24	14	servers	server	NOUN
ijassa-1239	24	15	)	)	PUNCT
ijassa-1239	24	16	.	.	PUNCT
ijassa-1239	25	1	most	most	ADJ
ijassa-1239	25	2	data	datum	NOUN
ijassa-1239	25	3	center	center	NOUN
ijassa-1239	25	4	services	service	NOUN
ijassa-1239	25	5	for	for	ADP
ijassa-1239	25	6	large	large	ADJ
ijassa-1239	25	7	-	-	PUNCT
ijassa-1239	25	8	scale	scale	NOUN
ijassa-1239	25	9	computing	computing	NOUN
ijassa-1239	25	10	are	be	AUX
ijassa-1239	25	11	based	base	VERB
ijassa-1239	25	12	on	on	ADP
ijassa-1239	25	13	fork	fork	NOUN
ijassa-1239	25	14	-	-	PUNCT
ijassa-1239	25	15	join	join	NOUN
ijassa-1239	25	16	structures	structure	NOUN
ijassa-1239	25	17	,	,	PUNCT
ijassa-1239	25	18	they	they	PRON
ijassa-1239	25	19	are	be	AUX
ijassa-1239	25	20	the	the	DET
ijassa-1239	25	21	main	main	ADJ
ijassa-1239	25	22	component	component	NOUN
ijassa-1239	25	23	of	of	ADP
ijassa-1239	25	24	the	the	DET
ijassa-1239	25	25	data	datum	NOUN
ijassa-1239	25	26	processing	processing	NOUN
ijassa-1239	25	27	of	of	ADP
ijassa-1239	25	28	parallel	parallel	ADJ
ijassa-1239	25	29	and/or	and/or	CCONJ
ijassa-1239	25	30	distributed	distribute	VERB
ijassa-1239	25	31	computing	computing	NOUN
ijassa-1239	25	32	systems	system	NOUN
ijassa-1239	25	33	.	.	PUNCT
ijassa-1239	26	1	a	a	DET
ijassa-1239	26	2	fork	fork	NOUN
ijassa-1239	26	3	-	-	PUNCT
ijassa-1239	26	4	join	join	NOUN
ijassa-1239	26	5	structure	structure	NOUN
ijassa-1239	26	6	is	be	AUX
ijassa-1239	26	7	understood	understand	VERB
ijassa-1239	26	8	as	as	ADP
ijassa-1239	26	9	a	a	DET
ijassa-1239	26	10	system	system	NOUN
ijassa-1239	26	11	,	,	PUNCT
ijassa-1239	26	12	upon	upon	SCONJ
ijassa-1239	26	13	entering	enter	VERB
ijassa-1239	26	14	which	which	PRON
ijassa-1239	26	15	the	the	DET
ijassa-1239	26	16	task	task	NOUN
ijassa-1239	26	17	is	be	AUX
ijassa-1239	26	18	divided	divide	VERB
ijassa-1239	26	19	into	into	ADP
ijassa-1239	26	20	parts	part	NOUN
ijassa-1239	26	21	–	–	PUNCT
ijassa-1239	26	22	independent	independent	ADJ
ijassa-1239	26	23	subtasks	subtask	NOUN
ijassa-1239	26	24	,	,	PUNCT
ijassa-1239	26	25	each	each	PRON
ijassa-1239	26	26	of	of	ADP
ijassa-1239	26	27	which	which	PRON
ijassa-1239	26	28	is	be	AUX
ijassa-1239	26	29	sent	send	VERB
ijassa-1239	26	30	for	for	ADP
ijassa-1239	26	31	service	service	NOUN
ijassa-1239	26	32	to	to	ADP
ijassa-1239	26	33	the	the	DET
ijassa-1239	26	34	corresponding	corresponding	ADJ
ijassa-1239	26	35	node	node	NOUN
ijassa-1239	26	36	.	.	PUNCT
ijassa-1239	27	1	the	the	DET
ijassa-1239	27	2	task	task	NOUN
ijassa-1239	27	3	is	be	AUX
ijassa-1239	27	4	considered	consider	VERB
ijassa-1239	27	5	completed	complete	VERB
ijassa-1239	27	6	after	after	ADP
ijassa-1239	27	7	processing	process	VERB
ijassa-1239	27	8	the	the	DET
ijassa-1239	27	9	last	last	NOUN
ijassa-1239	27	10	of	of	ADP
ijassa-1239	27	11	its	its	PRON
ijassa-1239	27	12	components	component	NOUN
ijassa-1239	27	13	.	.	PUNCT
ijassa-1239	28	1	thus	thus	ADV
ijassa-1239	28	2	,	,	PUNCT
ijassa-1239	28	3	the	the	DET
ijassa-1239	28	4	parallelization	parallelization	NOUN
ijassa-1239	28	5	of	of	ADP
ijassa-1239	28	6	data	datum	NOUN
ijassa-1239	28	7	or	or	CCONJ
ijassa-1239	28	8	tasks	task	NOUN
ijassa-1239	28	9	is	be	AUX
ijassa-1239	28	10	modeled	model	VERB
ijassa-1239	28	11	.	.	PUNCT
ijassa-1239	29	1	in	in	ADP
ijassa-1239	29	2	this	this	DET
ijassa-1239	29	3	case	case	NOUN
ijassa-1239	29	4	,	,	PUNCT
ijassa-1239	29	5	the	the	DET
ijassa-1239	29	6	processing	processing	NOUN
ijassa-1239	29	7	time	time	NOUN
ijassa-1239	29	8	of	of	ADP
ijassa-1239	29	9	the	the	DET
ijassa-1239	29	10	entire	entire	ADJ
ijassa-1239	29	11	task	task	NOUN
ijassa-1239	29	12	will	will	AUX
ijassa-1239	29	13	be	be	AUX
ijassa-1239	29	14	determined	determine	VERB
ijassa-1239	29	15	by	by	ADP
ijassa-1239	29	16	the	the	DET
ijassa-1239	29	17	maximum	maximum	NOUN
ijassa-1239	29	18	of	of	ADP
ijassa-1239	29	19	the	the	DET
ijassa-1239	29	20	processing	processing	NOUN
ijassa-1239	29	21	times	time	NOUN
ijassa-1239	29	22	of	of	ADP
ijassa-1239	29	23	its	its	PRON
ijassa-1239	29	24	subtasks	subtask	NOUN
ijassa-1239	29	25	.	.	PUNCT
ijassa-1239	30	1	from	from	ADP
ijassa-1239	30	2	the	the	DET
ijassa-1239	30	3	point	point	NOUN
ijassa-1239	30	4	of	of	ADP
ijassa-1239	30	5	view	view	NOUN
ijassa-1239	30	6	of	of	ADP
ijassa-1239	30	7	performance	performance	NOUN
ijassa-1239	30	8	and	and	CCONJ
ijassa-1239	30	9	efficient	efficient	ADJ
ijassa-1239	30	10	use	use	NOUN
ijassa-1239	30	11	of	of	ADP
ijassa-1239	30	12	resources	resource	NOUN
ijassa-1239	30	13	,	,	PUNCT
ijassa-1239	30	14	it	it	PRON
ijassa-1239	30	15	is	be	AUX
ijassa-1239	30	16	of	of	ADP
ijassa-1239	30	17	interest	interest	NOUN
ijassa-1239	30	18	to	to	PART
ijassa-1239	30	19	predict	predict	VERB
ijassa-1239	30	20	such	such	ADJ
ijassa-1239	30	21	characteristics	characteristic	NOUN
ijassa-1239	30	22	of	of	ADP
ijassa-1239	30	23	big	big	ADJ
ijassa-1239	30	24	data	datum	NOUN
ijassa-1239	30	25	analysis	analysis	NOUN
ijassa-1239	30	26	systems	system	NOUN
ijassa-1239	30	27	as	as	ADP
ijassa-1239	30	28	its	its	PRON
ijassa-1239	30	29	average	average	ADJ
ijassa-1239	30	30	response	response	NOUN
ijassa-1239	30	31	time	time	NOUN
ijassa-1239	30	32	,	,	PUNCT
ijassa-1239	30	33	including	include	VERB
ijassa-1239	30	34	in	in	ADP
ijassa-1239	30	35	the	the	DET
ijassa-1239	30	36	area	area	NOUN
ijassa-1239	30	37	of	of	ADP
ijassa-1239	30	38	high	high	ADJ
ijassa-1239	30	39	loads	load	NOUN
ijassa-1239	30	40	.	.	PUNCT
ijassa-1239	31	1	the	the	DET
ijassa-1239	31	2	equally	equally	ADV
ijassa-1239	31	3	important	important	ADJ
ijassa-1239	31	4	characteristic	characteristic	NOUN
ijassa-1239	31	5	that	that	PRON
ijassa-1239	31	6	needs	need	VERB
ijassa-1239	31	7	to	to	PART
ijassa-1239	31	8	be	be	AUX
ijassa-1239	31	9	evaluated	evaluate	VERB
ijassa-1239	31	10	is	be	AUX
ijassa-1239	31	11	the	the	DET
ijassa-1239	31	12	tail	tail	NOUN
ijassa-1239	31	13	of	of	ADP
ijassa-1239	31	14	latency	latency	NOUN
ijassa-1239	31	15	,	,	PUNCT
ijassa-1239	31	16	by	by	ADP
ijassa-1239	31	17	which	which	PRON
ijassa-1239	31	18	we	we	PRON
ijassa-1239	31	19	mean	mean	VERB
ijassa-1239	31	20	the	the	DET
ijassa-1239	31	21	99th	99th	ADJ
ijassa-1239	31	22	percentile	percentile	NOUN
ijassa-1239	31	23	of	of	ADP
ijassa-1239	31	24	the	the	DET
ijassa-1239	31	25	system	system	NOUN
ijassa-1239	31	26	response	response	NOUN
ijassa-1239	31	27	time	time	NOUN
ijassa-1239	31	28	distribution	distribution	NOUN
ijassa-1239	31	29	[	[	X
ijassa-1239	31	30	5	5	NUM
ijassa-1239	31	31	]	]	PUNCT
ijassa-1239	31	32	.	.	PUNCT
ijassa-1239	32	1	this	this	DET
ijassa-1239	32	2	article	article	NOUN
ijassa-1239	32	3	proposes	propose	VERB
ijassa-1239	32	4	the	the	DET
ijassa-1239	32	5	new	new	ADJ
ijassa-1239	32	6	approach	approach	NOUN
ijassa-1239	32	7	for	for	ADP
ijassa-1239	32	8	estimation	estimation	NOUN
ijassa-1239	32	9	of	of	ADP
ijassa-1239	32	10	the	the	DET
ijassa-1239	32	11	average	average	ADJ
ijassa-1239	32	12	response	response	NOUN
ijassa-1239	32	13	time	time	NOUN
ijassa-1239	32	14	and	and	CCONJ
ijassa-1239	32	15	its	its	PRON
ijassa-1239	32	16	tail	tail	NOUN
ijassa-1239	32	17	delay	delay	NOUN
ijassa-1239	32	18	for	for	ADP
ijassa-1239	32	19	data	data	NOUN
ijassa-1239	32	20	centers	center	NOUN
ijassa-1239	32	21	.	.	PUNCT
ijassa-1239	33	1	the	the	DET
ijassa-1239	33	2	approach	approach	NOUN
ijassa-1239	33	3	using	use	VERB
ijassa-1239	33	4	neural	neural	ADJ
ijassa-1239	33	5	networks	network	NOUN
ijassa-1239	33	6	allows	allow	VERB
ijassa-1239	33	7	one	one	NUM
ijassa-1239	33	8	to	to	PART
ijassa-1239	33	9	quickly	quickly	ADV
ijassa-1239	33	10	and	and	CCONJ
ijassa-1239	33	11	with	with	ADP
ijassa-1239	33	12	acceptable	acceptable	ADJ
ijassa-1239	33	13	accuracy	accuracy	NOUN
ijassa-1239	33	14	obtain	obtain	VERB
ijassa-1239	33	15	estimates	estimate	NOUN
ijassa-1239	33	16	of	of	ADP
ijassa-1239	33	17	the	the	DET
ijassa-1239	33	18	characteristics	characteristic	NOUN
ijassa-1239	33	19	of	of	ADP
ijassa-1239	33	20	interest	interest	NOUN
ijassa-1239	33	21	.	.	PUNCT
ijassa-1239	34	1	the	the	DET
ijassa-1239	34	2	advantage	advantage	NOUN
ijassa-1239	34	3	of	of	ADP
ijassa-1239	34	4	the	the	DET
ijassa-1239	34	5	approach	approach	NOUN
ijassa-1239	34	6	compared	compare	VERB
ijassa-1239	34	7	to	to	ADP
ijassa-1239	34	8	previously	previously	ADV
ijassa-1239	34	9	known	know	VERB
ijassa-1239	34	10	ones	one	NOUN
ijassa-1239	34	11	is	be	AUX
ijassa-1239	34	12	its	its	PRON
ijassa-1239	34	13	universality	universality	NOUN
ijassa-1239	34	14	,	,	PUNCT
ijassa-1239	34	15	since	since	SCONJ
ijassa-1239	34	16	there	there	PRON
ijassa-1239	34	17	are	be	VERB
ijassa-1239	34	18	no	no	DET
ijassa-1239	34	19	restrictions	restriction	NOUN
ijassa-1239	34	20	on	on	ADP
ijassa-1239	34	21	the	the	DET
ijassa-1239	34	22	architecture	architecture	NOUN
ijassa-1239	34	23	of	of	ADP
ijassa-1239	34	24	fork	fork	NOUN
ijassa-1239	34	25	-	-	PUNCT
ijassa-1239	34	26	join	join	NOUN
ijassa-1239	34	27	systems	system	NOUN
ijassa-1239	34	28	.	.	PUNCT
ijassa-1239	35	1	as	as	ADP
ijassa-1239	35	2	a	a	DET
ijassa-1239	35	3	result	result	NOUN
ijassa-1239	35	4	,	,	PUNCT
ijassa-1239	35	5	it	it	PRON
ijassa-1239	35	6	becomes	become	VERB
ijassa-1239	35	7	possible	possible	ADJ
ijassa-1239	35	8	to	to	PART
ijassa-1239	35	9	construct	construct	VERB
ijassa-1239	35	10	a	a	DET
ijassa-1239	35	11	more	more	ADV
ijassa-1239	35	12	realistic	realistic	ADJ
ijassa-1239	35	13	parallel	parallel	ADJ
ijassa-1239	35	14	computing	computing	NOUN
ijassa-1239	35	15	model	model	NOUN
ijassa-1239	35	16	based	base	VERB
ijassa-1239	35	17	on	on	ADP
ijassa-1239	35	18	practical	practical	ADJ
ijassa-1239	35	19	data	datum	NOUN
ijassa-1239	35	20	.	.	PUNCT
ijassa-1239	36	1	in	in	ADP
ijassa-1239	36	2	addition	addition	NOUN
ijassa-1239	36	3	,	,	PUNCT
ijassa-1239	36	4	you	you	PRON
ijassa-1239	36	5	can	can	AUX
ijassa-1239	36	6	achieve	achieve	VERB
ijassa-1239	36	7	good	good	ADJ
ijassa-1239	36	8	quality	quality	NOUN
ijassa-1239	36	9	estimates	estimate	NOUN
ijassa-1239	36	10	with	with	ADP
ijassa-1239	36	11	a	a	DET
ijassa-1239	36	12	basic	basic	ADJ
ijassa-1239	36	13	knowledge	knowledge	NOUN
ijassa-1239	36	14	of	of	ADP
ijassa-1239	36	15	neural	neural	ADJ
ijassa-1239	36	16	networks	network	NOUN
ijassa-1239	36	17	or	or	CCONJ
ijassa-1239	36	18	some	some	DET
ijassa-1239	36	19	other	other	ADJ
ijassa-1239	36	20	machine	machine	NOUN
ijassa-1239	36	21	learning	learning	NOUN
ijassa-1239	36	22	methods	method	NOUN
ijassa-1239	36	23	.	.	PUNCT
ijassa-1239	37	1	at	at	ADP
ijassa-1239	37	2	the	the	DET
ijassa-1239	37	3	same	same	ADJ
ijassa-1239	37	4	time	time	NOUN
ijassa-1239	37	5	,	,	PUNCT
ijassa-1239	37	6	the	the	DET
ijassa-1239	37	7	speed	speed	NOUN
ijassa-1239	37	8	of	of	ADP
ijassa-1239	37	9	the	the	DET
ijassa-1239	37	10	trained	train	VERB
ijassa-1239	37	11	neural	neural	ADJ
ijassa-1239	37	12	network	network	NOUN
ijassa-1239	37	13	is	be	AUX
ijassa-1239	37	14	comparable	comparable	ADJ
ijassa-1239	37	15	to	to	ADP
ijassa-1239	37	16	performing	perform	VERB
ijassa-1239	37	17	calculations	calculation	NOUN
ijassa-1239	37	18	using	use	VERB
ijassa-1239	37	19	a	a	DET
ijassa-1239	37	20	simple	simple	ADJ
ijassa-1239	37	21	analytical	analytical	ADJ
ijassa-1239	37	22	formula	formula	NOUN
ijassa-1239	37	23	,	,	PUNCT
ijassa-1239	37	24	as	as	SCONJ
ijassa-1239	37	25	opposed	oppose	VERB
ijassa-1239	37	26	to	to	ADP
ijassa-1239	37	27	the	the	DET
ijassa-1239	37	28	existing	exist	VERB
ijassa-1239	37	29	complex	complex	ADJ
ijassa-1239	37	30	computational	computational	ADJ
ijassa-1239	37	31	algorithms	algorithm	NOUN
ijassa-1239	37	32	.	.	PUNCT
ijassa-1239	38	1	the	the	DET
ijassa-1239	38	2	article	article	NOUN
ijassa-1239	38	3	is	be	AUX
ijassa-1239	38	4	organized	organize	VERB
ijassa-1239	38	5	as	as	SCONJ
ijassa-1239	38	6	follows	follow	VERB
ijassa-1239	38	7	:	:	PUNCT
ijassa-1239	38	8	the	the	DET
ijassa-1239	38	9	section	section	NOUN
ijassa-1239	38	10	2	2	NUM
ijassa-1239	38	11	describes	describe	VERB
ijassa-1239	38	12	the	the	DET
ijassa-1239	38	13	structure	structure	NOUN
ijassa-1239	38	14	of	of	ADP
ijassa-1239	38	15	the	the	DET
ijassa-1239	38	16	classical	classical	ADJ
ijassa-1239	38	17	fork	fork	NOUN
ijassa-1239	38	18	-	-	PUNCT
ijassa-1239	38	19	join	join	NOUN
ijassa-1239	38	20	qs	qs	NOUN
ijassa-1239	38	21	,	,	PUNCT
ijassa-1239	38	22	as	as	ADV
ijassa-1239	38	23	well	well	ADV
ijassa-1239	38	24	as	as	ADP
ijassa-1239	38	25	the	the	DET
ijassa-1239	38	26	main	main	ADJ
ijassa-1239	38	27	approaches	approach	NOUN
ijassa-1239	38	28	to	to	ADP
ijassa-1239	38	29	assessing	assess	VERB
ijassa-1239	38	30	its	its	PRON
ijassa-1239	38	31	characteristics	characteristic	NOUN
ijassa-1239	38	32	,	,	PUNCT
ijassa-1239	38	33	the	the	DET
ijassa-1239	38	34	section	section	NOUN
ijassa-1239	38	35	3	3	NUM
ijassa-1239	38	36	describes	describe	VERB
ijassa-1239	38	37	in	in	ADP
ijassa-1239	38	38	detail	detail	NOUN
ijassa-1239	38	39	the	the	DET
ijassa-1239	38	40	approach	approach	NOUN
ijassa-1239	38	41	proposed	propose	VERB
ijassa-1239	38	42	by	by	ADP
ijassa-1239	38	43	the	the	DET
ijassa-1239	38	44	authors	author	NOUN
ijassa-1239	38	45	of	of	ADP
ijassa-1239	38	46	using	use	VERB
ijassa-1239	38	47	artificial	artificial	ADJ
ijassa-1239	38	48	neural	neural	ADJ
ijassa-1239	38	49	networks	network	NOUN
ijassa-1239	38	50	(	(	PUNCT
ijassa-1239	38	51	ann	ann	PROPN
ijassa-1239	38	52	)	)	PUNCT
ijassa-1239	38	53	,	,	PUNCT
ijassa-1239	38	54	the	the	DET
ijassa-1239	38	55	section	section	NOUN
ijassa-1239	38	56	4	4	NUM
ijassa-1239	38	57	describes	describe	VERB
ijassa-1239	38	58	the	the	DET
ijassa-1239	38	59	mathematical	mathematical	ADJ
ijassa-1239	38	60	model	model	NOUN
ijassa-1239	38	61	of	of	ADP
ijassa-1239	38	62	the	the	DET
ijassa-1239	38	63	parallel	parallel	ADJ
ijassa-1239	38	64	structure	structure	NOUN
ijassa-1239	38	65	of	of	ADP
ijassa-1239	38	66	the	the	DET
ijassa-1239	38	67	big	big	ADJ
ijassa-1239	38	68	data	datum	NOUN
ijassa-1239	38	69	processing	processing	NOUN
ijassa-1239	38	70	center	center	NOUN
ijassa-1239	38	71	,	,	PUNCT
ijassa-1239	38	72	the	the	DET
ijassa-1239	38	73	section	section	NOUN
ijassa-1239	38	74	5	5	NUM
ijassa-1239	38	75	presents	present	VERB
ijassa-1239	38	76	the	the	DET
ijassa-1239	38	77	results	result	NOUN
ijassa-1239	38	78	of	of	ADP
ijassa-1239	38	79	numerous	numerous	ADJ
ijassa-1239	38	80	numerical	numerical	ADJ
ijassa-1239	38	81	experiments	experiment	NOUN
ijassa-1239	38	82	,	,	PUNCT
ijassa-1239	38	83	the	the	DET
ijassa-1239	38	84	section	section	NOUN
ijassa-1239	38	85	6	6	NUM
ijassa-1239	38	86	discusses	discuss	VERB
ijassa-1239	38	87	the	the	DET
ijassa-1239	38	88	features	feature	NOUN
ijassa-1239	38	89	of	of	ADP
ijassa-1239	38	90	the	the	DET
ijassa-1239	38	91	proposed	propose	VERB
ijassa-1239	38	92	approach	approach	NOUN
ijassa-1239	38	93	and	and	CCONJ
ijassa-1239	38	94	the	the	DET
ijassa-1239	38	95	prospects	prospect	NOUN
ijassa-1239	38	96	for	for	ADP
ijassa-1239	38	97	further	further	ADJ
ijassa-1239	38	98	research	research	NOUN
ijassa-1239	38	99	.	.	PUNCT
ijassa-1239	39	1	in	in	ADP
ijassa-1239	39	2	conclusion	conclusion	NOUN
ijassa-1239	39	3	,	,	PUNCT
ijassa-1239	39	4	some	some	DET
ijassa-1239	39	5	results	result	NOUN
ijassa-1239	39	6	are	be	AUX
ijassa-1239	39	7	summarized	summarize	VERB
ijassa-1239	39	8	.	.	PUNCT
ijassa-1239	40	1	2	2	X
ijassa-1239	40	2	.	.	X
ijassa-1239	40	3	related	relate	VERB
ijassa-1239	40	4	work	work	NOUN
ijassa-1239	40	5	most	most	ADJ
ijassa-1239	40	6	data	datum	NOUN
ijassa-1239	40	7	centers	center	NOUN
ijassa-1239	40	8	are	be	AUX
ijassa-1239	40	9	based	base	VERB
ijassa-1239	40	10	on	on	ADP
ijassa-1239	40	11	fork	fork	NOUN
ijassa-1239	40	12	-	-	PUNCT
ijassa-1239	40	13	join	join	NOUN
ijassa-1239	40	14	structures	structure	NOUN
ijassa-1239	40	15	.	.	PUNCT
ijassa-1239	41	1	by	by	ADP
ijassa-1239	41	2	a	a	DET
ijassa-1239	41	3	fork	fork	NOUN
ijassa-1239	41	4	-	-	PUNCT
ijassa-1239	41	5	join	join	NOUN
ijassa-1239	41	6	structure	structure	NOUN
ijassa-1239	41	7	(	(	PUNCT
ijassa-1239	41	8	system	system	NOUN
ijassa-1239	41	9	)	)	PUNCT
ijassa-1239	41	10	,	,	PUNCT
ijassa-1239	41	11	we	we	PRON
ijassa-1239	41	12	mean	mean	VERB
ijassa-1239	41	13	a	a	DET
ijassa-1239	41	14	queuing	queuing	NOUN
ijassa-1239	41	15	system	system	NOUN
ijassa-1239	41	16	,	,	PUNCT
ijassa-1239	41	17	each	each	DET
ijassa-1239	41	18	node	node	NOUN
ijassa-1239	41	19	of	of	ADP
ijassa-1239	41	20	which	which	PRON
ijassa-1239	41	21	is	be	AUX
ijassa-1239	41	22	an	an	DET
ijassa-1239	41	23	independent	independent	ADJ
ijassa-1239	41	24	qs	qs	NOUN
ijassa-1239	41	25	.	.	PUNCT
ijassa-1239	42	1	the	the	DET
ijassa-1239	42	2	fork	fork	NOUN
ijassa-1239	42	3	-	-	PUNCT
ijassa-1239	42	4	join	join	NOUN
ijassa-1239	42	5	type	type	NOUN
ijassa-1239	42	6	system	system	NOUN
ijassa-1239	42	7	functions	function	NOUN
ijassa-1239	42	8	as	as	SCONJ
ijassa-1239	42	9	follows	follow	VERB
ijassa-1239	42	10	(	(	PUNCT
ijassa-1239	42	11	fig	fig	NOUN
ijassa-1239	42	12	.	.	PUNCT
ijassa-1239	43	1	2.1	2.1	NUM
ijassa-1239	43	2	):	):	PUNCT
ijassa-1239	43	3	1	1	NUM
ijassa-1239	43	4	)	)	PUNCT
ijassa-1239	43	5	at	at	ADP
ijassa-1239	43	6	the	the	DET
ijassa-1239	43	7	moment	moment	NOUN
ijassa-1239	43	8	of	of	ADP
ijassa-1239	43	9	its	its	PRON
ijassa-1239	43	10	arrival	arrival	NOUN
ijassa-1239	43	11	a	a	DET
ijassa-1239	43	12	request	request	NOUN
ijassa-1239	43	13	is	be	AUX
ijassa-1239	43	14	instantly	instantly	ADV
ijassa-1239	43	15	split	split	VERB
ijassa-1239	43	16	into	into	ADP
ijassa-1239	43	17	k	k	PROPN
ijassa-1239	43	18	(	(	PUNCT
ijassa-1239	43	19	k	k	NOUN
ijassa-1239	43	20	⩾	⩾	ADJ
ijassa-1239	43	21	2	2	NUM
ijassa-1239	43	22	)	)	PUNCT
ijassa-1239	43	23	subtasks	subtask	NOUN
ijassa-1239	43	24	,	,	PUNCT
ijassa-1239	43	25	each	each	PRON
ijassa-1239	43	26	of	of	ADP
ijassa-1239	43	27	which	which	PRON
ijassa-1239	43	28	,	,	PUNCT
ijassa-1239	43	29	in	in	ADP
ijassa-1239	43	30	its	its	PRON
ijassa-1239	43	31	turn	turn	NOUN
ijassa-1239	43	32	,	,	PUNCT
ijassa-1239	43	33	is	be	AUX
ijassa-1239	43	34	queued	queue	VERB
ijassa-1239	43	35	for	for	ADP
ijassa-1239	43	36	future	future	ADJ
ijassa-1239	43	37	service	service	NOUN
ijassa-1239	43	38	;	;	PUNCT
ijassa-1239	43	39	2	2	X
ijassa-1239	43	40	)	)	PUNCT
ijassa-1239	43	41	after	after	ADP
ijassa-1239	43	42	the	the	DET
ijassa-1239	43	43	end	end	NOUN
ijassa-1239	43	44	of	of	ADP
ijassa-1239	43	45	the	the	DET
ijassa-1239	43	46	service	service	NOUN
ijassa-1239	43	47	,	,	PUNCT
ijassa-1239	43	48	the	the	DET
ijassa-1239	43	49	subtask	subtask	NOUN
ijassa-1239	43	50	enters	enter	VERB
ijassa-1239	43	51	the	the	DET
ijassa-1239	43	52	synchronization	synchronization	NOUN
ijassa-1239	43	53	buffer	buffer	NOUN
ijassa-1239	43	54	and	and	CCONJ
ijassa-1239	43	55	remains	remain	VERB
ijassa-1239	43	56	there	there	ADV
ijassa-1239	43	57	until	until	SCONJ
ijassa-1239	43	58	all	all	DET
ijassa-1239	43	59	related	related	ADJ
ijassa-1239	43	60	subtasks	subtask	NOUN
ijassa-1239	43	61	are	be	AUX
ijassa-1239	43	62	processed	process	VERB
ijassa-1239	43	63	,	,	PUNCT
ijassa-1239	43	64	i.e.	i.e.	X
ijassa-1239	43	65	only	only	ADV
ijassa-1239	43	66	after	after	ADP
ijassa-1239	43	67	that	that	SCONJ
ijassa-1239	43	68	the	the	DET
ijassa-1239	43	69	request	request	NOUN
ijassa-1239	43	70	is	be	AUX
ijassa-1239	43	71	considered	consider	VERB
ijassa-1239	43	72	to	to	PART
ijassa-1239	43	73	be	be	AUX
ijassa-1239	43	74	served	serve	VERB
ijassa-1239	43	75	and	and	CCONJ
ijassa-1239	43	76	can	can	AUX
ijassa-1239	43	77	leave	leave	VERB
ijassa-1239	43	78	the	the	DET
ijassa-1239	43	79	system	system	NOUN
ijassa-1239	43	80	.	.	PUNCT
ijassa-1239	44	1	a	a	DET
ijassa-1239	44	2	classical	classical	ADJ
ijassa-1239	44	3	fork	fork	NOUN
ijassa-1239	44	4	-	-	PUNCT
ijassa-1239	44	5	join	join	NOUN
ijassa-1239	44	6	qs	qs	NOUN
ijassa-1239	44	7	assumes	assume	NOUN
ijassa-1239	44	8	that	that	SCONJ
ijassa-1239	44	9	each	each	DET
ijassa-1239	44	10	subsystem	subsystem	NOUN
ijassa-1239	44	11	has	have	VERB
ijassa-1239	44	12	one	one	NUM
ijassa-1239	44	13	server	server	NOUN
ijassa-1239	44	14	.	.	PUNCT
ijassa-1239	45	1	we	we	PRON
ijassa-1239	45	2	will	will	AUX
ijassa-1239	45	3	expand	expand	VERB
ijassa-1239	45	4	this	this	DET
ijassa-1239	45	5	system	system	NOUN
ijassa-1239	45	6	to	to	ADP
ijassa-1239	45	7	the	the	DET
ijassa-1239	45	8	most	most	ADV
ijassa-1239	45	9	general	general	ADJ
ijassa-1239	45	10	case	case	NOUN
ijassa-1239	45	11	,	,	PUNCT
ijassa-1239	45	12	when	when	SCONJ
ijassa-1239	45	13	each	each	DET
ijassa-1239	45	14	qs	qs	NOUN
ijassa-1239	45	15	can	can	AUX
ijassa-1239	45	16	contain	contain	VERB
ijassa-1239	45	17	n	n	PRON
ijassa-1239	45	18	≥	≥	NUM
ijassa-1239	45	19	1	1	NUM
ijassa-1239	45	20	servers	server	NOUN
ijassa-1239	45	21	,	,	PUNCT
ijassa-1239	45	22	i.e.	i.e.	X
ijassa-1239	45	23	,	,	PUNCT
ijassa-1239	45	24	each	each	DET
ijassa-1239	45	25	subsystem	subsystem	NOUN
ijassa-1239	45	26	will	will	AUX
ijassa-1239	45	27	be	be	AUX
ijassa-1239	45	28	a	a	DET
ijassa-1239	45	29	qs	qs	NOUN
ijassa-1239	45	30	of	of	ADP
ijassa-1239	45	31	type	type	NOUN
ijassa-1239	45	32	g|g|n	g|g|n	PROPN
ijassa-1239	45	33	.	.	PUNCT
ijassa-1239	46	1	thus	thus	ADV
ijassa-1239	46	2	,	,	PUNCT
ijassa-1239	46	3	it	it	PRON
ijassa-1239	46	4	will	will	AUX
ijassa-1239	46	5	be	be	AUX
ijassa-1239	46	6	possible	possible	ADJ
ijassa-1239	46	7	to	to	PART
ijassa-1239	46	8	analyze	analyze	VERB
ijassa-1239	46	9	the	the	DET
ijassa-1239	46	10	characteristics	characteristic	NOUN
ijassa-1239	46	11	of	of	ADP
ijassa-1239	46	12	the	the	DET
ijassa-1239	46	13	system	system	NOUN
ijassa-1239	46	14	in	in	ADP
ijassa-1239	46	15	the	the	DET
ijassa-1239	46	16	conditions	condition	NOUN
ijassa-1239	46	17	of	of	ADP
ijassa-1239	46	18	allocation	allocation	NOUN
ijassa-1239	46	19	of	of	ADP
ijassa-1239	46	20	additional	additional	ADJ
ijassa-1239	46	21	resources	resource	NOUN
ijassa-1239	46	22	.	.	PUNCT
ijassa-1239	47	1	the	the	DET
ijassa-1239	47	2	results	result	NOUN
ijassa-1239	47	3	of	of	ADP
ijassa-1239	47	4	the	the	DET
ijassa-1239	47	5	study	study	NOUN
ijassa-1239	47	6	will	will	AUX
ijassa-1239	47	7	avoid	avoid	VERB
ijassa-1239	47	8	redundancy	redundancy	NOUN
ijassa-1239	47	9	in	in	ADP
ijassa-1239	47	10	their	their	PRON
ijassa-1239	47	11	selection	selection	NOUN
ijassa-1239	47	12	.	.	PUNCT
ijassa-1239	48	1	one	one	NUM
ijassa-1239	48	2	of	of	ADP
ijassa-1239	48	3	the	the	DET
ijassa-1239	48	4	first	first	ADJ
ijassa-1239	48	5	works	work	NOUN
ijassa-1239	48	6	devoted	devote	VERB
ijassa-1239	48	7	to	to	ADP
ijassa-1239	48	8	the	the	DET
ijassa-1239	48	9	analysis	analysis	NOUN
ijassa-1239	48	10	of	of	ADP
ijassa-1239	48	11	fork	fork	NOUN
ijassa-1239	48	12	-	-	PUNCT
ijassa-1239	48	13	join	join	NOUN
ijassa-1239	48	14	qs	qs	NOUN
ijassa-1239	48	15	with	with	ADP
ijassa-1239	48	16	subsystems	subsystem	NOUN
ijassa-1239	48	17	of	of	ADP
ijassa-1239	48	18	the	the	DET
ijassa-1239	48	19	form	form	NOUN
ijassa-1239	48	20	m	m	NOUN
ijassa-1239	48	21	|m	|m	NOUN
ijassa-1239	48	22	|1	|1	PRON
ijassa-1239	48	23	is	be	AUX
ijassa-1239	48	24	the	the	DET
ijassa-1239	48	25	article	article	NOUN
ijassa-1239	48	26	[	[	X
ijassa-1239	48	27	14	14	NUM
ijassa-1239	48	28	]	]	PUNCT
ijassa-1239	48	29	.	.	PUNCT
ijassa-1239	49	1	here	here	ADV
ijassa-1239	49	2	,	,	PUNCT
ijassa-1239	49	3	exact	exact	ADJ
ijassa-1239	49	4	expressions	expression	NOUN
ijassa-1239	49	5	were	be	AUX
ijassa-1239	49	6	obtained	obtain	VERB
ijassa-1239	49	7	for	for	ADP
ijassa-1239	49	8	estimating	estimate	VERB
ijassa-1239	49	9	the	the	DET
ijassa-1239	49	10	copyright	copyright	NOUN
ijassa-1239	49	11	©	©	ADP
ijassa-1239	49	12	2022	2022	NUM
ijassa-1239	49	13	assa	assa	NOUN
ijassa-1239	49	14	.	.	PUNCT
ijassa-1239	50	1	adv	adv	PROPN
ijassa-1239	50	2	syst	syst	PROPN
ijassa-1239	50	3	sci	sci	PROPN
ijassa-1239	50	4	appl	appl	PROPN
ijassa-1239	50	5	(	(	PUNCT
ijassa-1239	50	6	2022	2022	NUM
ijassa-1239	50	7	)	)	PUNCT
ijassa-1239	50	8	72	72	NUM
ijassa-1239	50	9	a.v	a.v	PROPN
ijassa-1239	50	10	.	.	PROPN
ijassa-1239	50	11	gorbunova	gorbunova	PROPN
ijassa-1239	50	12	,	,	PUNCT
ijassa-1239	50	13	v.m	v.m	PROPN
ijassa-1239	50	14	.	.	PUNCT
ijassa-1239	50	15	vishnevsky	vishnevsky	PROPN
ijassa-1239	50	16	.	.	PUNCT
ijassa-1239	50	17	.	.	PUNCT
ijassa-1239	50	18	.	.	PUNCT
ijassa-1239	51	1	fork	fork	PROPN
ijassa-1239	51	2	point	point	NOUN
ijassa-1239	51	3	join	join	NOUN
ijassa-1239	51	4	point	point	NOUN
ijassa-1239	51	5	...	...	PUNCT
ijassa-1239	51	6	...	...	PUNCT
ijassa-1239	52	1	...	...	PUNCT
ijassa-1239	52	2	fig	fig	NOUN
ijassa-1239	52	3	.	.	PUNCT
ijassa-1239	53	1	2.1	2.1	NUM
ijassa-1239	53	2	.	.	PUNCT
ijassa-1239	53	3	fork	fork	NOUN
ijassa-1239	53	4	-	-	PUNCT
ijassa-1239	53	5	join	join	NOUN
ijassa-1239	53	6	system	system	NOUN
ijassa-1239	53	7	model	model	NOUN
ijassa-1239	53	8	.	.	PUNCT
ijassa-1239	54	1	mean	mean	VERB
ijassa-1239	54	2	response	response	NOUN
ijassa-1239	54	3	time	time	NOUN
ijassa-1239	54	4	of	of	ADP
ijassa-1239	54	5	the	the	DET
ijassa-1239	54	6	system	system	NOUN
ijassa-1239	54	7	in	in	ADP
ijassa-1239	54	8	the	the	DET
ijassa-1239	54	9	case	case	NOUN
ijassa-1239	54	10	of	of	ADP
ijassa-1239	54	11	two	two	NUM
ijassa-1239	54	12	subsystems	subsystem	NOUN
ijassa-1239	54	13	m	m	VERB
ijassa-1239	54	14	|m	|m	NOUN
ijassa-1239	54	15	|1	|1	NUM
ijassa-1239	54	16	,	,	PUNCT
ijassa-1239	54	17	k	k	NOUN
ijassa-1239	54	18	=	=	NOUN
ijassa-1239	54	19	2	2	X
ijassa-1239	54	20	.	.	PUNCT
ijassa-1239	55	1	in	in	ADP
ijassa-1239	55	2	most	most	ADJ
ijassa-1239	55	3	of	of	ADP
ijassa-1239	55	4	the	the	DET
ijassa-1239	55	5	following	follow	VERB
ijassa-1239	55	6	works	work	NOUN
ijassa-1239	55	7	on	on	ADP
ijassa-1239	55	8	the	the	DET
ijassa-1239	55	9	subject	subject	NOUN
ijassa-1239	55	10	of	of	ADP
ijassa-1239	55	11	fork	fork	NOUN
ijassa-1239	55	12	-	-	PUNCT
ijassa-1239	55	13	join	join	NOUN
ijassa-1239	55	14	qs	qs	NOUN
ijassa-1239	55	15	,	,	PUNCT
ijassa-1239	55	16	various	various	ADJ
ijassa-1239	55	17	methods	method	NOUN
ijassa-1239	55	18	were	be	AUX
ijassa-1239	55	19	used	use	VERB
ijassa-1239	55	20	to	to	PART
ijassa-1239	55	21	obtain	obtain	VERB
ijassa-1239	55	22	only	only	ADJ
ijassa-1239	55	23	approximations	approximation	NOUN
ijassa-1239	55	24	of	of	ADP
ijassa-1239	55	25	the	the	DET
ijassa-1239	55	26	mean	mean	ADJ
ijassa-1239	55	27	response	response	NOUN
ijassa-1239	55	28	time	time	NOUN
ijassa-1239	55	29	for	for	ADP
ijassa-1239	55	30	k	k	PROPN
ijassa-1239	55	31	>	>	X
ijassa-1239	55	32	2	2	X
ijassa-1239	55	33	.	.	PUNCT
ijassa-1239	55	34	for	for	ADP
ijassa-1239	55	35	a	a	DET
ijassa-1239	55	36	detailed	detailed	ADJ
ijassa-1239	55	37	overview	overview	NOUN
ijassa-1239	55	38	of	of	ADP
ijassa-1239	55	39	publications	publication	NOUN
ijassa-1239	55	40	up	up	ADP
ijassa-1239	55	41	to	to	ADP
ijassa-1239	55	42	2014	2014	NUM
ijassa-1239	55	43	,	,	PUNCT
ijassa-1239	55	44	see	see	VERB
ijassa-1239	55	45	[	[	X
ijassa-1239	55	46	20	20	NUM
ijassa-1239	55	47	]	]	PUNCT
ijassa-1239	55	48	.	.	PUNCT
ijassa-1239	56	1	among	among	ADP
ijassa-1239	56	2	the	the	DET
ijassa-1239	56	3	main	main	ADJ
ijassa-1239	56	4	approximate	approximate	ADJ
ijassa-1239	56	5	methods	method	NOUN
ijassa-1239	56	6	for	for	ADP
ijassa-1239	56	7	studying	study	VERB
ijassa-1239	56	8	fork	fork	NOUN
ijassa-1239	56	9	-	-	PUNCT
ijassa-1239	56	10	join	join	NOUN
ijassa-1239	56	11	qs	qs	NOUN
ijassa-1239	56	12	with	with	ADP
ijassa-1239	56	13	k	k	PROPN
ijassa-1239	56	14	subsystems	subsystem	NOUN
ijassa-1239	56	15	of	of	ADP
ijassa-1239	56	16	the	the	DET
ijassa-1239	56	17	form	form	NOUN
ijassa-1239	56	18	m	m	NOUN
ijassa-1239	56	19	|m	|m	NOUN
ijassa-1239	56	20	|1	|1	PRON
ijassa-1239	56	21	or	or	CCONJ
ijassa-1239	56	22	m	m	PROPN
ijassa-1239	56	23	|g|1	|g|1	PROPN
ijassa-1239	56	24	are	be	AUX
ijassa-1239	56	25	:	:	PUNCT
ijassa-1239	56	26	matrix	matrix	NOUN
ijassa-1239	56	27	-	-	PUNCT
ijassa-1239	56	28	geometric	geometric	ADJ
ijassa-1239	56	29	approach	approach	NOUN
ijassa-1239	56	30	,	,	PUNCT
ijassa-1239	56	31	interpolation	interpolation	NOUN
ijassa-1239	56	32	based	base	VERB
ijassa-1239	56	33	on	on	ADP
ijassa-1239	56	34	data	datum	NOUN
ijassa-1239	56	35	obtained	obtain	VERB
ijassa-1239	56	36	in	in	ADP
ijassa-1239	56	37	extreme	extreme	ADJ
ijassa-1239	56	38	cases	case	NOUN
ijassa-1239	56	39	of	of	ADP
ijassa-1239	56	40	high	high	ADJ
ijassa-1239	56	41	and	and	CCONJ
ijassa-1239	56	42	low	low	ADJ
ijassa-1239	56	43	input	input	NOUN
ijassa-1239	56	44	loads	load	NOUN
ijassa-1239	56	45	,	,	PUNCT
ijassa-1239	56	46	an	an	DET
ijassa-1239	56	47	approach	approach	NOUN
ijassa-1239	56	48	using	use	VERB
ijassa-1239	56	49	elements	element	NOUN
ijassa-1239	56	50	of	of	ADP
ijassa-1239	56	51	the	the	DET
ijassa-1239	56	52	theory	theory	NOUN
ijassa-1239	56	53	of	of	ADP
ijassa-1239	56	54	order	order	NOUN
ijassa-1239	56	55	statistics	statistic	NOUN
ijassa-1239	57	1	[	[	X
ijassa-1239	57	2	6	6	NUM
ijassa-1239	57	3	]	]	PUNCT
ijassa-1239	57	4	,	,	PUNCT
ijassa-1239	57	5	an	an	DET
ijassa-1239	57	6	empirical	empirical	ADJ
ijassa-1239	57	7	approach	approach	NOUN
ijassa-1239	57	8	(	(	PUNCT
ijassa-1239	57	9	construction	construction	NOUN
ijassa-1239	57	10	of	of	ADP
ijassa-1239	57	11	analytical	analytical	ADJ
ijassa-1239	57	12	formulas	formula	NOUN
ijassa-1239	57	13	based	base	VERB
ijassa-1239	57	14	on	on	ADP
ijassa-1239	57	15	data	datum	NOUN
ijassa-1239	57	16	obtained	obtain	VERB
ijassa-1239	57	17	by	by	ADP
ijassa-1239	57	18	simulation	simulation	NOUN
ijassa-1239	57	19	)	)	PUNCT
ijassa-1239	57	20	,	,	PUNCT
ijassa-1239	57	21	etc	etc	X
ijassa-1239	57	22	.	.	X
ijassa-1239	57	23	note	note	VERB
ijassa-1239	57	24	that	that	SCONJ
ijassa-1239	57	25	there	there	PRON
ijassa-1239	57	26	are	be	VERB
ijassa-1239	57	27	no	no	DET
ijassa-1239	57	28	exact	exact	ADJ
ijassa-1239	57	29	solutions	solution	NOUN
ijassa-1239	57	30	for	for	ADP
ijassa-1239	57	31	the	the	DET
ijassa-1239	57	32	mean	mean	ADJ
ijassa-1239	57	33	response	response	NOUN
ijassa-1239	57	34	time	time	NOUN
ijassa-1239	57	35	even	even	ADV
ijassa-1239	57	36	in	in	ADP
ijassa-1239	57	37	the	the	DET
ijassa-1239	57	38	case	case	NOUN
ijassa-1239	57	39	of	of	ADP
ijassa-1239	57	40	exponential	exponential	ADJ
ijassa-1239	57	41	incoming	incoming	ADJ
ijassa-1239	57	42	and	and	CCONJ
ijassa-1239	57	43	servicing	servicing	NOUN
ijassa-1239	57	44	flows	flow	NOUN
ijassa-1239	57	45	for	for	ADP
ijassa-1239	57	46	k	k	PROPN
ijassa-1239	57	47	>	>	X
ijassa-1239	57	48	2	2	X
ijassa-1239	57	49	.	.	PUNCT
ijassa-1239	58	1	the	the	DET
ijassa-1239	58	2	complexity	complexity	NOUN
ijassa-1239	58	3	of	of	ADP
ijassa-1239	58	4	the	the	DET
ijassa-1239	58	5	analysis	analysis	NOUN
ijassa-1239	58	6	is	be	AUX
ijassa-1239	58	7	explained	explain	VERB
ijassa-1239	58	8	by	by	ADP
ijassa-1239	58	9	the	the	DET
ijassa-1239	58	10	dependence	dependence	NOUN
ijassa-1239	58	11	of	of	ADP
ijassa-1239	58	12	the	the	DET
ijassa-1239	58	13	residence	residence	NOUN
ijassa-1239	58	14	times	time	NOUN
ijassa-1239	58	15	of	of	ADP
ijassa-1239	58	16	subtasks	subtask	NOUN
ijassa-1239	58	17	in	in	ADP
ijassa-1239	58	18	subsystems	subsystem	NOUN
ijassa-1239	58	19	due	due	ADP
ijassa-1239	58	20	to	to	ADP
ijassa-1239	58	21	their	their	PRON
ijassa-1239	58	22	common	common	ADJ
ijassa-1239	58	23	moments	moment	NOUN
ijassa-1239	58	24	of	of	ADP
ijassa-1239	58	25	arrival	arrival	NOUN
ijassa-1239	58	26	.	.	PUNCT
ijassa-1239	59	1	therefore	therefore	ADV
ijassa-1239	59	2	,	,	PUNCT
ijassa-1239	59	3	the	the	DET
ijassa-1239	59	4	analytical	analytical	ADJ
ijassa-1239	59	5	approach	approach	NOUN
ijassa-1239	59	6	is	be	AUX
ijassa-1239	59	7	based	base	VERB
ijassa-1239	59	8	,	,	PUNCT
ijassa-1239	59	9	as	as	ADP
ijassa-1239	59	10	a	a	DET
ijassa-1239	59	11	rule	rule	NOUN
ijassa-1239	59	12	,	,	PUNCT
ijassa-1239	59	13	on	on	ADP
ijassa-1239	59	14	the	the	DET
ijassa-1239	59	15	assumption	assumption	NOUN
ijassa-1239	59	16	of	of	ADP
ijassa-1239	59	17	the	the	DET
ijassa-1239	59	18	absence	absence	NOUN
ijassa-1239	59	19	of	of	ADP
ijassa-1239	59	20	this	this	DET
ijassa-1239	59	21	dependence	dependence	NOUN
ijassa-1239	59	22	.	.	PUNCT
ijassa-1239	60	1	as	as	ADP
ijassa-1239	60	2	a	a	DET
ijassa-1239	60	3	result	result	NOUN
ijassa-1239	60	4	,	,	PUNCT
ijassa-1239	60	5	the	the	DET
ijassa-1239	60	6	application	application	NOUN
ijassa-1239	60	7	of	of	ADP
ijassa-1239	60	8	the	the	DET
ijassa-1239	60	9	estimates	estimate	NOUN
ijassa-1239	60	10	obtained	obtain	VERB
ijassa-1239	60	11	is	be	AUX
ijassa-1239	60	12	limited	limit	VERB
ijassa-1239	60	13	either	either	ADV
ijassa-1239	60	14	by	by	ADP
ijassa-1239	60	15	the	the	DET
ijassa-1239	60	16	number	number	NOUN
ijassa-1239	60	17	of	of	ADP
ijassa-1239	60	18	subsystems	subsystem	NOUN
ijassa-1239	60	19	k	k	PROPN
ijassa-1239	60	20	,	,	PUNCT
ijassa-1239	60	21	or	or	CCONJ
ijassa-1239	60	22	by	by	ADP
ijassa-1239	60	23	the	the	DET
ijassa-1239	60	24	specific	specific	ADJ
ijassa-1239	60	25	type	type	NOUN
ijassa-1239	60	26	of	of	ADP
ijassa-1239	60	27	distribution	distribution	NOUN
ijassa-1239	60	28	of	of	ADP
ijassa-1239	60	29	the	the	DET
ijassa-1239	60	30	servicing	servicing	NOUN
ijassa-1239	60	31	flow	flow	NOUN
ijassa-1239	60	32	,	,	PUNCT
ijassa-1239	60	33	or	or	CCONJ
ijassa-1239	60	34	by	by	ADP
ijassa-1239	60	35	insufficient	insufficient	ADJ
ijassa-1239	60	36	approximation	approximation	NOUN
ijassa-1239	60	37	accuracy	accuracy	NOUN
ijassa-1239	60	38	.	.	PUNCT
ijassa-1239	61	1	this	this	PRON
ijassa-1239	61	2	narrows	narrow	VERB
ijassa-1239	61	3	the	the	DET
ijassa-1239	61	4	scope	scope	NOUN
ijassa-1239	61	5	of	of	ADP
ijassa-1239	61	6	the	the	DET
ijassa-1239	61	7	obtained	obtain	VERB
ijassa-1239	61	8	analytical	analytical	ADJ
ijassa-1239	61	9	expressions	expression	NOUN
ijassa-1239	61	10	.	.	PUNCT
ijassa-1239	62	1	in	in	ADP
ijassa-1239	62	2	particular	particular	ADJ
ijassa-1239	62	3	,	,	PUNCT
ijassa-1239	62	4	there	there	PRON
ijassa-1239	62	5	are	be	VERB
ijassa-1239	62	6	problems	problem	NOUN
ijassa-1239	62	7	with	with	ADP
ijassa-1239	62	8	modern	modern	ADJ
ijassa-1239	62	9	systems	system	NOUN
ijassa-1239	62	10	due	due	ADJ
ijassa-1239	62	11	to	to	ADP
ijassa-1239	62	12	heavy	heavy	ADJ
ijassa-1239	62	13	-	-	PUNCT
ijassa-1239	62	14	tailed	tail	VERB
ijassa-1239	62	15	distributions	distribution	NOUN
ijassa-1239	62	16	.	.	PUNCT
ijassa-1239	63	1	as	as	ADP
ijassa-1239	63	2	for	for	ADP
ijassa-1239	63	3	the	the	DET
ijassa-1239	63	4	case	case	NOUN
ijassa-1239	63	5	with	with	ADP
ijassa-1239	63	6	subsystems	subsystem	NOUN
ijassa-1239	63	7	of	of	ADP
ijassa-1239	63	8	a	a	DET
ijassa-1239	63	9	more	more	ADV
ijassa-1239	63	10	general	general	ADJ
ijassa-1239	63	11	form	form	NOUN
ijassa-1239	63	12	,	,	PUNCT
ijassa-1239	63	13	i.e.	i.e.	X
ijassa-1239	63	14	,	,	PUNCT
ijassa-1239	63	15	g|g|1	g|g|1	NOUN
ijassa-1239	63	16	,	,	PUNCT
ijassa-1239	63	17	there	there	PRON
ijassa-1239	63	18	are	be	VERB
ijassa-1239	63	19	very	very	ADV
ijassa-1239	63	20	few	few	ADJ
ijassa-1239	63	21	studies	study	NOUN
ijassa-1239	63	22	on	on	ADP
ijassa-1239	63	23	this	this	DET
ijassa-1239	63	24	topic	topic	NOUN
ijassa-1239	63	25	and	and	CCONJ
ijassa-1239	63	26	they	they	PRON
ijassa-1239	63	27	have	have	AUX
ijassa-1239	63	28	appeared	appear	VERB
ijassa-1239	63	29	mainly	mainly	ADV
ijassa-1239	63	30	in	in	ADP
ijassa-1239	63	31	recent	recent	ADJ
ijassa-1239	63	32	times	time	NOUN
ijassa-1239	63	33	.	.	PUNCT
ijassa-1239	64	1	fork	fork	NOUN
ijassa-1239	64	2	-	-	PUNCT
ijassa-1239	64	3	join	join	NOUN
ijassa-1239	64	4	cmo	cmo	NOUN
ijassa-1239	64	5	is	be	AUX
ijassa-1239	64	6	a	a	DET
ijassa-1239	64	7	natural	natural	ADJ
ijassa-1239	64	8	model	model	NOUN
ijassa-1239	64	9	for	for	ADP
ijassa-1239	64	10	many	many	ADJ
ijassa-1239	64	11	real	real	ADJ
ijassa-1239	64	12	-	-	PUNCT
ijassa-1239	64	13	life	life	NOUN
ijassa-1239	64	14	systems	system	NOUN
ijassa-1239	64	15	in	in	ADP
ijassa-1239	64	16	various	various	ADJ
ijassa-1239	64	17	areas	area	NOUN
ijassa-1239	64	18	where	where	SCONJ
ijassa-1239	64	19	parallel	parallel	ADJ
ijassa-1239	64	20	processing	processing	NOUN
ijassa-1239	64	21	of	of	ADP
ijassa-1239	64	22	tasks	task	NOUN
ijassa-1239	64	23	is	be	AUX
ijassa-1239	64	24	carried	carry	VERB
ijassa-1239	64	25	out	out	ADP
ijassa-1239	64	26	in	in	ADP
ijassa-1239	64	27	order	order	NOUN
ijassa-1239	64	28	to	to	PART
ijassa-1239	64	29	improve	improve	VERB
ijassa-1239	64	30	performance	performance	NOUN
ijassa-1239	64	31	.	.	PUNCT
ijassa-1239	65	1	in	in	ADP
ijassa-1239	65	2	this	this	DET
ijassa-1239	65	3	case	case	NOUN
ijassa-1239	65	4	,	,	PUNCT
ijassa-1239	65	5	we	we	PRON
ijassa-1239	65	6	are	be	AUX
ijassa-1239	65	7	talking	talk	VERB
ijassa-1239	65	8	not	not	PART
ijassa-1239	65	9	only	only	ADV
ijassa-1239	65	10	about	about	ADP
ijassa-1239	65	11	telecommunication	telecommunication	NOUN
ijassa-1239	65	12	systems	system	NOUN
ijassa-1239	65	13	,	,	PUNCT
ijassa-1239	65	14	but	but	CCONJ
ijassa-1239	65	15	also	also	ADV
ijassa-1239	65	16	about	about	ADP
ijassa-1239	65	17	production	production	NOUN
ijassa-1239	65	18	areas	area	NOUN
ijassa-1239	65	19	(	(	PUNCT
ijassa-1239	65	20	assembly	assembly	NOUN
ijassa-1239	65	21	of	of	ADP
ijassa-1239	65	22	orders	order	NOUN
ijassa-1239	65	23	,	,	PUNCT
ijassa-1239	65	24	logistics	logistic	NOUN
ijassa-1239	65	25	,	,	PUNCT
ijassa-1239	65	26	etc	etc	X
ijassa-1239	65	27	.	.	X
ijassa-1239	65	28	)	)	PUNCT
ijassa-1239	65	29	.	.	PUNCT
ijassa-1239	66	1	therefore	therefore	ADV
ijassa-1239	66	2	,	,	PUNCT
ijassa-1239	66	3	despite	despite	SCONJ
ijassa-1239	66	4	a	a	DET
ijassa-1239	66	5	slight	slight	ADJ
ijassa-1239	66	6	decrease	decrease	NOUN
ijassa-1239	66	7	in	in	ADP
ijassa-1239	66	8	the	the	DET
ijassa-1239	66	9	activity	activity	NOUN
ijassa-1239	66	10	of	of	ADP
ijassa-1239	66	11	research	research	NOUN
ijassa-1239	66	12	in	in	ADP
ijassa-1239	66	13	this	this	DET
ijassa-1239	66	14	direction	direction	NOUN
ijassa-1239	66	15	,	,	PUNCT
ijassa-1239	66	16	their	their	PRON
ijassa-1239	66	17	relevance	relevance	NOUN
ijassa-1239	66	18	is	be	AUX
ijassa-1239	66	19	still	still	ADV
ijassa-1239	66	20	great	great	ADJ
ijassa-1239	66	21	.	.	PUNCT
ijassa-1239	67	1	among	among	ADP
ijassa-1239	67	2	the	the	DET
ijassa-1239	67	3	recent	recent	ADJ
ijassa-1239	67	4	works	work	NOUN
ijassa-1239	67	5	devoted	devote	VERB
ijassa-1239	67	6	to	to	ADP
ijassa-1239	67	7	this	this	DET
ijassa-1239	67	8	subject	subject	NOUN
ijassa-1239	67	9	,	,	PUNCT
ijassa-1239	67	10	it	it	PRON
ijassa-1239	67	11	is	be	AUX
ijassa-1239	67	12	worth	worth	ADJ
ijassa-1239	67	13	noting	note	VERB
ijassa-1239	67	14	the	the	DET
ijassa-1239	67	15	following	following	NOUN
ijassa-1239	67	16	.	.	PUNCT
ijassa-1239	68	1	[	[	X
ijassa-1239	68	2	18	18	NUM
ijassa-1239	68	3	]	]	PUNCT
ijassa-1239	68	4	proposes	propose	VERB
ijassa-1239	68	5	an	an	DET
ijassa-1239	68	6	approach	approach	NOUN
ijassa-1239	68	7	for	for	ADP
ijassa-1239	68	8	approximating	approximate	VERB
ijassa-1239	68	9	the	the	DET
ijassa-1239	68	10	distribution	distribution	NOUN
ijassa-1239	68	11	of	of	ADP
ijassa-1239	68	12	response	response	NOUN
ijassa-1239	68	13	time	time	NOUN
ijassa-1239	68	14	in	in	ADP
ijassa-1239	68	15	the	the	DET
ijassa-1239	68	16	case	case	NOUN
ijassa-1239	68	17	of	of	ADP
ijassa-1239	68	18	homogeneous	homogeneous	ADJ
ijassa-1239	68	19	k	k	PROPN
ijassa-1239	68	20	fork	fork	NOUN
ijassa-1239	68	21	-	-	PUNCT
ijassa-1239	68	22	join	join	NOUN
ijassa-1239	68	23	nodes	node	NOUN
ijassa-1239	68	24	of	of	ADP
ijassa-1239	68	25	a	a	DET
ijassa-1239	68	26	qs	qs	NOUN
ijassa-1239	68	27	of	of	ADP
ijassa-1239	68	28	the	the	DET
ijassa-1239	68	29	form	form	NOUN
ijassa-1239	68	30	map	map	NOUN
ijassa-1239	68	31	|ph|1	|ph|1	NOUN
ijassa-1239	68	32	.	.	NOUN
ijassa-1239	69	1	numerical	numerical	ADJ
ijassa-1239	69	2	experiments	experiment	NOUN
ijassa-1239	69	3	have	have	AUX
ijassa-1239	69	4	shown	show	VERB
ijassa-1239	69	5	that	that	SCONJ
ijassa-1239	69	6	the	the	DET
ijassa-1239	69	7	method	method	NOUN
ijassa-1239	69	8	is	be	AUX
ijassa-1239	69	9	quite	quite	ADV
ijassa-1239	69	10	accurate	accurate	ADJ
ijassa-1239	69	11	mainly	mainly	ADV
ijassa-1239	69	12	for	for	ADP
ijassa-1239	69	13	tail	tail	NOUN
ijassa-1239	69	14	delays	delay	NOUN
ijassa-1239	69	15	.	.	PUNCT
ijassa-1239	70	1	it	it	PRON
ijassa-1239	70	2	is	be	AUX
ijassa-1239	70	3	based	base	VERB
ijassa-1239	70	4	on	on	ADP
ijassa-1239	70	5	analytical	analytical	ADJ
ijassa-1239	70	6	results	result	NOUN
ijassa-1239	70	7	only	only	ADV
ijassa-1239	70	8	for	for	ADP
ijassa-1239	70	9	k	k	PROPN
ijassa-1239	70	10	=	=	SYM
ijassa-1239	70	11	1	1	NUM
ijassa-1239	70	12	and	and	CCONJ
ijassa-1239	70	13	k	k	NOUN
ijassa-1239	70	14	=	=	NOUN
ijassa-1239	70	15	2	2	X
ijassa-1239	70	16	.	.	PUNCT
ijassa-1239	71	1	the	the	DET
ijassa-1239	71	2	accuracy	accuracy	NOUN
ijassa-1239	71	3	of	of	ADP
ijassa-1239	71	4	the	the	DET
ijassa-1239	71	5	algorithm	algorithm	NOUN
ijassa-1239	71	6	developed	develop	VERB
ijassa-1239	71	7	by	by	ADP
ijassa-1239	71	8	the	the	DET
ijassa-1239	71	9	authors	author	NOUN
ijassa-1239	71	10	of	of	ADP
ijassa-1239	71	11	the	the	DET
ijassa-1239	71	12	article	article	NOUN
ijassa-1239	71	13	depends	depend	VERB
ijassa-1239	71	14	on	on	ADP
ijassa-1239	71	15	the	the	DET
ijassa-1239	71	16	choice	choice	NOUN
ijassa-1239	71	17	of	of	ADP
ijassa-1239	71	18	the	the	DET
ijassa-1239	71	19	constant	constant	ADJ
ijassa-1239	71	20	c.	c.	NOUN
ijassa-1239	71	21	the	the	PRON
ijassa-1239	71	22	larger	large	ADJ
ijassa-1239	71	23	the	the	DET
ijassa-1239	71	24	value	value	NOUN
ijassa-1239	71	25	of	of	ADP
ijassa-1239	71	26	this	this	DET
ijassa-1239	71	27	constant	constant	ADJ
ijassa-1239	71	28	,	,	PUNCT
ijassa-1239	71	29	the	the	PRON
ijassa-1239	71	30	higher	high	ADJ
ijassa-1239	71	31	the	the	DET
ijassa-1239	71	32	accuracy	accuracy	NOUN
ijassa-1239	71	33	of	of	ADP
ijassa-1239	71	34	the	the	DET
ijassa-1239	71	35	resulting	result	VERB
ijassa-1239	71	36	estimates	estimate	NOUN
ijassa-1239	71	37	.	.	PUNCT
ijassa-1239	72	1	however	however	ADV
ijassa-1239	72	2	,	,	PUNCT
ijassa-1239	72	3	this	this	PRON
ijassa-1239	72	4	significantly	significantly	ADV
ijassa-1239	72	5	increases	increase	VERB
ijassa-1239	72	6	the	the	DET
ijassa-1239	72	7	complexity	complexity	NOUN
ijassa-1239	72	8	of	of	ADP
ijassa-1239	72	9	the	the	DET
ijassa-1239	72	10	algorithm	algorithm	NOUN
ijassa-1239	72	11	itself	itself	PRON
ijassa-1239	72	12	and	and	CCONJ
ijassa-1239	72	13	,	,	PUNCT
ijassa-1239	72	14	accordingly	accordingly	ADV
ijassa-1239	72	15	,	,	PUNCT
ijassa-1239	72	16	the	the	DET
ijassa-1239	72	17	running	running	ADJ
ijassa-1239	72	18	time	time	NOUN
ijassa-1239	72	19	of	of	ADP
ijassa-1239	72	20	its	its	PRON
ijassa-1239	72	21	software	software	NOUN
ijassa-1239	72	22	implementation	implementation	NOUN
ijassa-1239	72	23	,	,	PUNCT
ijassa-1239	72	24	since	since	SCONJ
ijassa-1239	72	25	it	it	PRON
ijassa-1239	72	26	contains	contain	VERB
ijassa-1239	72	27	operations	operation	NOUN
ijassa-1239	72	28	with	with	ADP
ijassa-1239	72	29	high	high	ADJ
ijassa-1239	72	30	-	-	PUNCT
ijassa-1239	72	31	dimensional	dimensional	ADJ
ijassa-1239	72	32	matrices	matrix	NOUN
ijassa-1239	72	33	.	.	PUNCT
ijassa-1239	73	1	the	the	DET
ijassa-1239	73	2	quality	quality	NOUN
ijassa-1239	73	3	of	of	ADP
ijassa-1239	73	4	the	the	DET
ijassa-1239	73	5	tail	tail	NOUN
ijassa-1239	73	6	delay	delay	NOUN
ijassa-1239	73	7	approximation	approximation	NOUN
ijassa-1239	73	8	also	also	ADV
ijassa-1239	73	9	depends	depend	VERB
ijassa-1239	73	10	on	on	ADP
ijassa-1239	73	11	the	the	DET
ijassa-1239	73	12	choice	choice	NOUN
ijassa-1239	73	13	of	of	ADP
ijassa-1239	73	14	specific	specific	ADJ
ijassa-1239	73	15	distributions	distribution	NOUN
ijassa-1239	73	16	,	,	PUNCT
ijassa-1239	73	17	the	the	DET
ijassa-1239	73	18	load	load	NOUN
ijassa-1239	73	19	level	level	NOUN
ijassa-1239	73	20	,	,	PUNCT
ijassa-1239	73	21	and	and	CCONJ
ijassa-1239	73	22	the	the	DET
ijassa-1239	73	23	value	value	NOUN
ijassa-1239	73	24	of	of	ADP
ijassa-1239	73	25	k.	k.	PROPN
ijassa-1239	73	26	as	as	ADP
ijassa-1239	73	27	k	k	PROPN
ijassa-1239	73	28	increases	increase	NOUN
ijassa-1239	73	29	,	,	PUNCT
ijassa-1239	73	30	the	the	DET
ijassa-1239	73	31	error	error	NOUN
ijassa-1239	73	32	increases	increase	NOUN
ijassa-1239	73	33	,	,	PUNCT
ijassa-1239	73	34	but	but	CCONJ
ijassa-1239	73	35	,	,	PUNCT
ijassa-1239	73	36	for	for	ADP
ijassa-1239	73	37	example	example	NOUN
ijassa-1239	73	38	,	,	PUNCT
ijassa-1239	73	39	for	for	ADP
ijassa-1239	73	40	large	large	ADJ
ijassa-1239	73	41	values	value	NOUN
ijassa-1239	73	42	of	of	ADP
ijassa-1239	73	43	k	k	NOUN
ijassa-1239	73	44	,	,	PUNCT
ijassa-1239	73	45	the	the	DET
ijassa-1239	73	46	error	error	NOUN
ijassa-1239	73	47	does	do	AUX
ijassa-1239	73	48	not	not	PART
ijassa-1239	73	49	exceed	exceed	VERB
ijassa-1239	73	50	15	15	NUM
ijassa-1239	73	51	%	%	NOUN
ijassa-1239	73	52	in	in	ADP
ijassa-1239	73	53	the	the	DET
ijassa-1239	73	54	case	case	NOUN
ijassa-1239	73	55	of	of	ADP
ijassa-1239	73	56	the	the	DET
ijassa-1239	73	57	erlang	erlang	PROPN
ijassa-1239	73	58	distribution	distribution	NOUN
ijassa-1239	73	59	of	of	ADP
ijassa-1239	73	60	service	service	NOUN
ijassa-1239	73	61	time	time	NOUN
ijassa-1239	73	62	.	.	PUNCT
ijassa-1239	74	1	and	and	CCONJ
ijassa-1239	74	2	for	for	ADP
ijassa-1239	74	3	the	the	DET
ijassa-1239	74	4	hyperexponential	hyperexponential	ADJ
ijassa-1239	74	5	service	service	NOUN
ijassa-1239	74	6	time	time	NOUN
ijassa-1239	74	7	distribution	distribution	NOUN
ijassa-1239	74	8	,	,	PUNCT
ijassa-1239	74	9	the	the	DET
ijassa-1239	74	10	approximation	approximation	NOUN
ijassa-1239	74	11	error	error	NOUN
ijassa-1239	74	12	does	do	AUX
ijassa-1239	74	13	not	not	PART
ijassa-1239	74	14	exceed	exceed	VERB
ijassa-1239	74	15	5	5	NUM
ijassa-1239	74	16	%	%	NOUN
ijassa-1239	74	17	.	.	PUNCT
ijassa-1239	75	1	copyright	copyright	NOUN
ijassa-1239	75	2	©	©	ADP
ijassa-1239	75	3	2022	2022	NUM
ijassa-1239	75	4	assa	assa	NOUN
ijassa-1239	75	5	.	.	PUNCT
ijassa-1239	76	1	adv	adv	PROPN
ijassa-1239	76	2	syst	syst	PROPN
ijassa-1239	76	3	sci	sci	PROPN
ijassa-1239	76	4	appl	appl	PROPN
ijassa-1239	76	5	(	(	PUNCT
ijassa-1239	76	6	2022	2022	NUM
ijassa-1239	76	7	)	)	PUNCT
ijassa-1239	76	8	the	the	DET
ijassa-1239	76	9	analysis	analysis	NOUN
ijassa-1239	76	10	of	of	ADP
ijassa-1239	76	11	big	big	ADJ
ijassa-1239	76	12	data	datum	NOUN
ijassa-1239	76	13	centers	center	NOUN
ijassa-1239	76	14	performance	performance	VERB
ijassa-1239	76	15	73	73	NUM
ijassa-1239	76	16	the	the	DET
ijassa-1239	76	17	article	article	NOUN
ijassa-1239	76	18	[	[	X
ijassa-1239	76	19	22	22	NUM
ijassa-1239	76	20	]	]	PUNCT
ijassa-1239	76	21	explores	explore	VERB
ijassa-1239	76	22	two	two	NUM
ijassa-1239	76	23	modes	mode	NOUN
ijassa-1239	76	24	of	of	ADP
ijassa-1239	76	25	operation	operation	NOUN
ijassa-1239	76	26	of	of	ADP
ijassa-1239	76	27	the	the	DET
ijassa-1239	76	28	fork	fork	NOUN
ijassa-1239	76	29	-	-	PUNCT
ijassa-1239	76	30	join	join	VERB
ijassa-1239	76	31	qs	qs	NOUN
ijassa-1239	76	32	with	with	ADP
ijassa-1239	76	33	subsystems	subsystem	NOUN
ijassa-1239	76	34	of	of	ADP
ijassa-1239	76	35	the	the	DET
ijassa-1239	76	36	form	form	NOUN
ijassa-1239	76	37	m	m	VERB
ijassa-1239	76	38	|g|1	|g|1	PROPN
ijassa-1239	76	39	,	,	PUNCT
ijassa-1239	76	40	in	in	ADP
ijassa-1239	76	41	which	which	PRON
ijassa-1239	76	42	requests	request	NOUN
ijassa-1239	76	43	can	can	AUX
ijassa-1239	76	44	be	be	AUX
ijassa-1239	76	45	split	split	VERB
ijassa-1239	76	46	into	into	ADP
ijassa-1239	76	47	subtasks	subtask	NOUN
ijassa-1239	76	48	,	,	PUNCT
ijassa-1239	76	49	the	the	DET
ijassa-1239	76	50	number	number	NOUN
ijassa-1239	76	51	of	of	ADP
ijassa-1239	76	52	which	which	PRON
ijassa-1239	76	53	is	be	AUX
ijassa-1239	76	54	less	less	ADJ
ijassa-1239	76	55	than	than	ADP
ijassa-1239	76	56	or	or	CCONJ
ijassa-1239	76	57	equal	equal	ADJ
ijassa-1239	76	58	to	to	ADP
ijassa-1239	76	59	the	the	DET
ijassa-1239	76	60	total	total	ADJ
ijassa-1239	76	61	number	number	NOUN
ijassa-1239	76	62	of	of	ADP
ijassa-1239	76	63	servers	server	NOUN
ijassa-1239	76	64	in	in	ADP
ijassa-1239	76	65	the	the	DET
ijassa-1239	76	66	qs	qs	NOUN
ijassa-1239	76	67	.	.	NOUN
ijassa-1239	76	68	propositions	proposition	NOUN
ijassa-1239	76	69	about	about	ADP
ijassa-1239	76	70	the	the	DET
ijassa-1239	76	71	asymptotic	asymptotic	ADJ
ijassa-1239	76	72	independence	independence	NOUN
ijassa-1239	76	73	of	of	ADP
ijassa-1239	76	74	the	the	DET
ijassa-1239	76	75	sojourn	sojourn	NOUN
ijassa-1239	76	76	times	time	NOUN
ijassa-1239	76	77	of	of	ADP
ijassa-1239	76	78	subtasks	subtask	NOUN
ijassa-1239	76	79	(	(	PUNCT
ijassa-1239	76	80	when	when	SCONJ
ijassa-1239	76	81	the	the	DET
ijassa-1239	76	82	number	number	NOUN
ijassa-1239	76	83	of	of	ADP
ijassa-1239	76	84	servers	server	NOUN
ijassa-1239	76	85	tends	tend	VERB
ijassa-1239	76	86	to	to	PART
ijassa-1239	76	87	infinity	infinity	VERB
ijassa-1239	76	88	)	)	PUNCT
ijassa-1239	76	89	are	be	AUX
ijassa-1239	76	90	proved	prove	VERB
ijassa-1239	76	91	,	,	PUNCT
ijassa-1239	76	92	and	and	CCONJ
ijassa-1239	76	93	an	an	DET
ijassa-1239	76	94	upper	upper	ADJ
ijassa-1239	76	95	bound	bind	VERB
ijassa-1239	76	96	on	on	ADP
ijassa-1239	76	97	the	the	DET
ijassa-1239	76	98	mean	mean	ADJ
ijassa-1239	76	99	response	response	NOUN
ijassa-1239	76	100	time	time	NOUN
ijassa-1239	76	101	for	for	SCONJ
ijassa-1239	76	102	this	this	DET
ijassa-1239	76	103	system	system	NOUN
ijassa-1239	76	104	is	be	AUX
ijassa-1239	76	105	obtained	obtain	VERB
ijassa-1239	76	106	.	.	PUNCT
ijassa-1239	77	1	in	in	ADP
ijassa-1239	77	2	[	[	X
ijassa-1239	77	3	8	8	NUM
ijassa-1239	77	4	]	]	PUNCT
ijassa-1239	77	5	for	for	ADP
ijassa-1239	77	6	the	the	DET
ijassa-1239	77	7	fork	fork	NOUN
ijassa-1239	77	8	-	-	PUNCT
ijassa-1239	77	9	join	join	NOUN
ijassa-1239	77	10	qs	qs	NOUN
ijassa-1239	77	11	with	with	ADP
ijassa-1239	77	12	two	two	NUM
ijassa-1239	77	13	subsystems	subsystem	NOUN
ijassa-1239	77	14	m	m	VERB
ijassa-1239	77	15	|g|1	|g|1	ADJ
ijassa-1239	77	16	and	and	CCONJ
ijassa-1239	77	17	non	non	ADJ
ijassa-1239	77	18	-	-	ADJ
ijassa-1239	77	19	homogeneous	homogeneous	ADJ
ijassa-1239	77	20	servers	server	NOUN
ijassa-1239	77	21	,	,	PUNCT
ijassa-1239	77	22	the	the	DET
ijassa-1239	77	23	remaining	remain	VERB
ijassa-1239	77	24	service	service	NOUN
ijassa-1239	77	25	time	time	NOUN
ijassa-1239	77	26	is	be	AUX
ijassa-1239	77	27	analyzed	analyze	VERB
ijassa-1239	77	28	,	,	PUNCT
ijassa-1239	77	29	which	which	PRON
ijassa-1239	77	30	is	be	AUX
ijassa-1239	77	31	necessary	necessary	ADJ
ijassa-1239	77	32	for	for	ADP
ijassa-1239	77	33	the	the	DET
ijassa-1239	77	34	correct	correct	ADJ
ijassa-1239	77	35	shutdown	shutdown	NOUN
ijassa-1239	77	36	of	of	ADP
ijassa-1239	77	37	the	the	DET
ijassa-1239	77	38	system	system	NOUN
ijassa-1239	77	39	in	in	ADP
ijassa-1239	77	40	the	the	DET
ijassa-1239	77	41	event	event	NOUN
ijassa-1239	77	42	of	of	ADP
ijassa-1239	77	43	a	a	DET
ijassa-1239	77	44	disconnection	disconnection	NOUN
ijassa-1239	77	45	of	of	ADP
ijassa-1239	77	46	the	the	DET
ijassa-1239	77	47	incoming	incoming	ADJ
ijassa-1239	77	48	flow	flow	NOUN
ijassa-1239	77	49	.	.	PUNCT
ijassa-1239	78	1	the	the	DET
ijassa-1239	78	2	asymptotic	asymptotic	ADJ
ijassa-1239	78	3	independence	independence	NOUN
ijassa-1239	78	4	of	of	ADP
ijassa-1239	78	5	the	the	DET
ijassa-1239	78	6	maximum	maximum	ADJ
ijassa-1239	78	7	residual	residual	ADJ
ijassa-1239	78	8	service	service	NOUN
ijassa-1239	78	9	times	time	NOUN
ijassa-1239	78	10	for	for	ADP
ijassa-1239	78	11	a	a	DET
ijassa-1239	78	12	high	high	ADJ
ijassa-1239	78	13	system	system	NOUN
ijassa-1239	78	14	load	load	NOUN
ijassa-1239	78	15	is	be	AUX
ijassa-1239	78	16	proved	prove	VERB
ijassa-1239	78	17	.	.	PUNCT
ijassa-1239	79	1	the	the	DET
ijassa-1239	79	2	article	article	NOUN
ijassa-1239	79	3	[	[	X
ijassa-1239	79	4	15	15	NUM
ijassa-1239	79	5	]	]	PUNCT
ijassa-1239	79	6	proposes	propose	VERB
ijassa-1239	79	7	an	an	DET
ijassa-1239	79	8	approach	approach	NOUN
ijassa-1239	79	9	for	for	ADP
ijassa-1239	79	10	estimating	estimate	VERB
ijassa-1239	79	11	the	the	DET
ijassa-1239	79	12	average	average	ADJ
ijassa-1239	79	13	response	response	NOUN
ijassa-1239	79	14	time	time	NOUN
ijassa-1239	79	15	and	and	CCONJ
ijassa-1239	79	16	its	its	PRON
ijassa-1239	79	17	tail	tail	NOUN
ijassa-1239	79	18	delay	delay	NOUN
ijassa-1239	79	19	fork	fork	NOUN
ijassa-1239	79	20	-	-	PUNCT
ijassa-1239	79	21	join	join	VERB
ijassa-1239	79	22	qs	qs	NOUN
ijassa-1239	79	23	with	with	ADP
ijassa-1239	79	24	g|g|n	g|g|n	NOUN
ijassa-1239	79	25	subsystems	subsystem	NOUN
ijassa-1239	79	26	as	as	ADP
ijassa-1239	79	27	a	a	DET
ijassa-1239	79	28	model	model	NOUN
ijassa-1239	79	29	of	of	ADP
ijassa-1239	79	30	some	some	DET
ijassa-1239	79	31	data	datum	NOUN
ijassa-1239	79	32	center	center	NOUN
ijassa-1239	79	33	.	.	PUNCT
ijassa-1239	80	1	in	in	ADP
ijassa-1239	80	2	this	this	DET
ijassa-1239	80	3	case	case	NOUN
ijassa-1239	80	4	,	,	PUNCT
ijassa-1239	80	5	each	each	DET
ijassa-1239	80	6	qs	qs	ADP
ijassa-1239	80	7	node	node	NOUN
ijassa-1239	80	8	is	be	AUX
ijassa-1239	80	9	proposed	propose	VERB
ijassa-1239	80	10	to	to	PART
ijassa-1239	80	11	be	be	AUX
ijassa-1239	80	12	considered	consider	VERB
ijassa-1239	80	13	either	either	CCONJ
ijassa-1239	80	14	as	as	ADP
ijassa-1239	80	15	a	a	DET
ijassa-1239	80	16	white	white	PROPN
ijassa-1239	80	17	box	box	PROPN
ijassa-1239	80	18	model	model	NOUN
ijassa-1239	80	19	,	,	PUNCT
ijassa-1239	80	20	i.e.	i.e.	X
ijassa-1239	80	21	,	,	PUNCT
ijassa-1239	80	22	under	under	ADP
ijassa-1239	80	23	conditions	condition	NOUN
ijassa-1239	80	24	where	where	SCONJ
ijassa-1239	80	25	the	the	DET
ijassa-1239	80	26	type	type	NOUN
ijassa-1239	80	27	of	of	ADP
ijassa-1239	80	28	service	service	NOUN
ijassa-1239	80	29	time	time	NOUN
ijassa-1239	80	30	distribution	distribution	NOUN
ijassa-1239	80	31	is	be	AUX
ijassa-1239	80	32	known	know	VERB
ijassa-1239	80	33	.	.	PUNCT
ijassa-1239	81	1	in	in	ADP
ijassa-1239	81	2	the	the	DET
ijassa-1239	81	3	second	second	ADJ
ijassa-1239	81	4	variant	variant	NOUN
ijassa-1239	81	5	(	(	PUNCT
ijassa-1239	81	6	when	when	SCONJ
ijassa-1239	81	7	there	there	PRON
ijassa-1239	81	8	are	be	VERB
ijassa-1239	81	9	no	no	DET
ijassa-1239	81	10	assumptions	assumption	NOUN
ijassa-1239	81	11	about	about	ADP
ijassa-1239	81	12	the	the	DET
ijassa-1239	81	13	structure	structure	NOUN
ijassa-1239	81	14	of	of	ADP
ijassa-1239	81	15	the	the	DET
ijassa-1239	81	16	node	node	NOUN
ijassa-1239	81	17	,	,	PUNCT
ijassa-1239	81	18	namely	namely	ADV
ijassa-1239	81	19	,	,	PUNCT
ijassa-1239	81	20	about	about	ADP
ijassa-1239	81	21	the	the	DET
ijassa-1239	81	22	type	type	NOUN
ijassa-1239	81	23	of	of	ADP
ijassa-1239	81	24	service	service	NOUN
ijassa-1239	81	25	time	time	NOUN
ijassa-1239	81	26	distribution	distribution	NOUN
ijassa-1239	81	27	on	on	ADP
ijassa-1239	81	28	it	it	PRON
ijassa-1239	81	29	)	)	PUNCT
ijassa-1239	81	30	,	,	PUNCT
ijassa-1239	81	31	it	it	PRON
ijassa-1239	81	32	is	be	AUX
ijassa-1239	81	33	assumed	assume	VERB
ijassa-1239	81	34	that	that	SCONJ
ijassa-1239	81	35	we	we	PRON
ijassa-1239	81	36	are	be	AUX
ijassa-1239	81	37	dealing	deal	VERB
ijassa-1239	81	38	with	with	ADP
ijassa-1239	81	39	a	a	DET
ijassa-1239	81	40	node	node	ADJ
ijassa-1239	81	41	model	model	NOUN
ijassa-1239	81	42	as	as	ADP
ijassa-1239	81	43	a	a	DET
ijassa-1239	81	44	black	black	ADJ
ijassa-1239	81	45	box	box	NOUN
ijassa-1239	81	46	.	.	PUNCT
ijassa-1239	82	1	in	in	ADP
ijassa-1239	82	2	this	this	DET
ijassa-1239	82	3	case	case	NOUN
ijassa-1239	82	4	,	,	PUNCT
ijassa-1239	82	5	it	it	PRON
ijassa-1239	82	6	is	be	AUX
ijassa-1239	82	7	proposed	propose	VERB
ijassa-1239	82	8	to	to	PART
ijassa-1239	82	9	estimate	estimate	VERB
ijassa-1239	82	10	the	the	DET
ijassa-1239	82	11	mean	mean	ADJ
ijassa-1239	82	12	values	value	NOUN
ijassa-1239	82	13	and	and	CCONJ
ijassa-1239	82	14	variance	variance	NOUN
ijassa-1239	82	15	of	of	ADP
ijassa-1239	82	16	the	the	DET
ijassa-1239	82	17	response	response	NOUN
ijassa-1239	82	18	time	time	NOUN
ijassa-1239	82	19	of	of	ADP
ijassa-1239	82	20	an	an	DET
ijassa-1239	82	21	individual	individual	ADJ
ijassa-1239	82	22	node	node	NOUN
ijassa-1239	82	23	empirically	empirically	ADV
ijassa-1239	82	24	.	.	PUNCT
ijassa-1239	83	1	in	in	ADP
ijassa-1239	83	2	other	other	ADJ
ijassa-1239	83	3	words	word	NOUN
ijassa-1239	83	4	,	,	PUNCT
ijassa-1239	83	5	it	it	PRON
ijassa-1239	83	6	is	be	AUX
ijassa-1239	83	7	proposed	propose	VERB
ijassa-1239	83	8	to	to	PART
ijassa-1239	83	9	represent	represent	VERB
ijassa-1239	83	10	each	each	DET
ijassa-1239	83	11	node	node	NOUN
ijassa-1239	83	12	as	as	ADP
ijassa-1239	83	13	a	a	DET
ijassa-1239	83	14	qs	qs	NOUN
ijassa-1239	83	15	of	of	ADP
ijassa-1239	83	16	the	the	DET
ijassa-1239	83	17	form	form	NOUN
ijassa-1239	83	18	g|g|1	g|g|1	NOUN
ijassa-1239	83	19	by	by	ADP
ijassa-1239	83	20	measuring	measure	VERB
ijassa-1239	83	21	the	the	DET
ijassa-1239	83	22	first	first	ADJ
ijassa-1239	83	23	two	two	NUM
ijassa-1239	83	24	response	response	NOUN
ijassa-1239	83	25	times	time	NOUN
ijassa-1239	83	26	of	of	ADP
ijassa-1239	83	27	the	the	DET
ijassa-1239	83	28	node	node	NOUN
ijassa-1239	83	29	of	of	ADP
ijassa-1239	83	30	the	the	DET
ijassa-1239	83	31	system	system	NOUN
ijassa-1239	83	32	under	under	ADP
ijassa-1239	83	33	study	study	NOUN
ijassa-1239	83	34	,	,	PUNCT
ijassa-1239	83	35	which	which	PRON
ijassa-1239	83	36	is	be	AUX
ijassa-1239	83	37	technically	technically	ADV
ijassa-1239	83	38	feasible	feasible	ADJ
ijassa-1239	83	39	.	.	PUNCT
ijassa-1239	84	1	in	in	ADP
ijassa-1239	84	2	accordance	accordance	NOUN
ijassa-1239	84	3	with	with	ADP
ijassa-1239	84	4	numerical	numerical	ADJ
ijassa-1239	84	5	experiments	experiment	NOUN
ijassa-1239	84	6	,	,	PUNCT
ijassa-1239	84	7	the	the	DET
ijassa-1239	84	8	approximation	approximation	NOUN
ijassa-1239	84	9	error	error	NOUN
ijassa-1239	84	10	of	of	ADP
ijassa-1239	84	11	the	the	DET
ijassa-1239	84	12	estimated	estimate	VERB
ijassa-1239	84	13	response	response	NOUN
ijassa-1239	84	14	time	time	NOUN
ijassa-1239	84	15	characteristics	characteristic	NOUN
ijassa-1239	84	16	in	in	ADP
ijassa-1239	84	17	the	the	DET
ijassa-1239	84	18	region	region	NOUN
ijassa-1239	84	19	of	of	ADP
ijassa-1239	84	20	high	high	ADJ
ijassa-1239	84	21	loads	load	NOUN
ijassa-1239	84	22	(	(	PUNCT
ijassa-1239	84	23	above	above	ADP
ijassa-1239	84	24	0.8	0.8	NUM
ijassa-1239	84	25	for	for	ADP
ijassa-1239	84	26	the	the	DET
ijassa-1239	84	27	average	average	ADJ
ijassa-1239	84	28	response	response	NOUN
ijassa-1239	84	29	time	time	NOUN
ijassa-1239	84	30	and	and	CCONJ
ijassa-1239	84	31	above	above	ADP
ijassa-1239	84	32	0.9	0.9	NUM
ijassa-1239	84	33	for	for	ADP
ijassa-1239	84	34	the	the	DET
ijassa-1239	84	35	tail	tail	NOUN
ijassa-1239	84	36	delay	delay	NOUN
ijassa-1239	84	37	)	)	PUNCT
ijassa-1239	84	38	does	do	AUX
ijassa-1239	84	39	not	not	PART
ijassa-1239	84	40	exceed	exceed	VERB
ijassa-1239	84	41	20	20	NUM
ijassa-1239	84	42	%	%	NOUN
ijassa-1239	84	43	and	and	CCONJ
ijassa-1239	84	44	15	15	NUM
ijassa-1239	84	45	%	%	NOUN
ijassa-1239	84	46	,	,	PUNCT
ijassa-1239	84	47	respectively	respectively	ADV
ijassa-1239	84	48	.	.	PUNCT
ijassa-1239	85	1	in	in	ADP
ijassa-1239	85	2	the	the	DET
ijassa-1239	85	3	articles	article	NOUN
ijassa-1239	85	4	[	[	X
ijassa-1239	85	5	10	10	NUM
ijassa-1239	85	6	]	]	PUNCT
ijassa-1239	85	7	and	and	CCONJ
ijassa-1239	85	8	[	[	X
ijassa-1239	85	9	9	9	NUM
ijassa-1239	85	10	]	]	PUNCT
ijassa-1239	85	11	for	for	ADP
ijassa-1239	85	12	the	the	DET
ijassa-1239	85	13	study	study	NOUN
ijassa-1239	85	14	of	of	ADP
ijassa-1239	85	15	fork	fork	NOUN
ijassa-1239	85	16	-	-	PUNCT
ijassa-1239	85	17	join	join	VERB
ijassa-1239	85	18	qs	qs	NOUN
ijassa-1239	85	19	with	with	ADP
ijassa-1239	85	20	subsystems	subsystem	NOUN
ijassa-1239	85	21	of	of	ADP
ijassa-1239	85	22	type	type	NOUN
ijassa-1239	85	23	m	m	NOUN
ijassa-1239	85	24	|m	|m	NOUN
ijassa-1239	85	25	|1	|1	NUM
ijassa-1239	85	26	in	in	ADP
ijassa-1239	85	27	the	the	DET
ijassa-1239	85	28	first	first	ADJ
ijassa-1239	85	29	case	case	NOUN
ijassa-1239	85	30	and	and	CCONJ
ijassa-1239	85	31	m	m	PROPN
ijassa-1239	85	32	|g|1	|g|1	ADJ
ijassa-1239	85	33	in	in	ADP
ijassa-1239	85	34	the	the	DET
ijassa-1239	85	35	second	second	NOUN
ijassa-1239	85	36	,	,	PUNCT
ijassa-1239	85	37	the	the	DET
ijassa-1239	85	38	approach	approach	NOUN
ijassa-1239	85	39	based	base	VERB
ijassa-1239	85	40	on	on	ADP
ijassa-1239	85	41	neural	neural	ADJ
ijassa-1239	85	42	networks	network	NOUN
ijassa-1239	85	43	is	be	AUX
ijassa-1239	85	44	proposed	propose	VERB
ijassa-1239	85	45	.	.	PUNCT
ijassa-1239	86	1	the	the	DET
ijassa-1239	86	2	results	result	NOUN
ijassa-1239	86	3	of	of	ADP
ijassa-1239	86	4	numerical	numerical	ADJ
ijassa-1239	86	5	experiments	experiment	NOUN
ijassa-1239	86	6	showed	show	VERB
ijassa-1239	86	7	a	a	DET
ijassa-1239	86	8	good	good	ADJ
ijassa-1239	86	9	quality	quality	NOUN
ijassa-1239	86	10	of	of	ADP
ijassa-1239	86	11	approximation	approximation	NOUN
ijassa-1239	86	12	,	,	PUNCT
ijassa-1239	86	13	which	which	PRON
ijassa-1239	86	14	prompted	prompt	VERB
ijassa-1239	86	15	the	the	DET
ijassa-1239	86	16	authors	author	NOUN
ijassa-1239	86	17	of	of	ADP
ijassa-1239	86	18	the	the	DET
ijassa-1239	86	19	article	article	NOUN
ijassa-1239	86	20	to	to	PART
ijassa-1239	86	21	conduct	conduct	VERB
ijassa-1239	86	22	a	a	DET
ijassa-1239	86	23	new	new	ADJ
ijassa-1239	86	24	study	study	NOUN
ijassa-1239	86	25	in	in	ADP
ijassa-1239	86	26	relation	relation	NOUN
ijassa-1239	86	27	to	to	PART
ijassa-1239	86	28	estimating	estimate	VERB
ijassa-1239	86	29	the	the	DET
ijassa-1239	86	30	performance	performance	NOUN
ijassa-1239	86	31	of	of	ADP
ijassa-1239	86	32	data	datum	NOUN
ijassa-1239	86	33	processing	processing	NOUN
ijassa-1239	86	34	centers	center	NOUN
ijassa-1239	86	35	with	with	ADP
ijassa-1239	86	36	parallel	parallel	ADJ
ijassa-1239	86	37	structures	structure	NOUN
ijassa-1239	86	38	,	,	PUNCT
ijassa-1239	86	39	the	the	DET
ijassa-1239	86	40	nodes	node	NOUN
ijassa-1239	86	41	of	of	ADP
ijassa-1239	86	42	which	which	PRON
ijassa-1239	86	43	are	be	AUX
ijassa-1239	86	44	modeled	model	VERB
ijassa-1239	86	45	by	by	ADP
ijassa-1239	86	46	general	general	ADJ
ijassa-1239	86	47	systems	system	NOUN
ijassa-1239	86	48	of	of	ADP
ijassa-1239	86	49	the	the	DET
ijassa-1239	86	50	g|g|n	g|g|n	PROPN
ijassa-1239	86	51	type	type	NOUN
ijassa-1239	86	52	.	.	PUNCT
ijassa-1239	87	1	3	3	X
ijassa-1239	87	2	.	.	X
ijassa-1239	87	3	analysis	analysis	NOUN
ijassa-1239	87	4	method	method	NOUN
ijassa-1239	87	5	of	of	ADP
ijassa-1239	87	6	fork	fork	NOUN
ijassa-1239	87	7	-	-	PUNCT
ijassa-1239	87	8	join	join	NOUN
ijassa-1239	87	9	qs	qs	NOUN
ijassa-1239	87	10	using	use	VERB
ijassa-1239	87	11	neural	neural	ADJ
ijassa-1239	87	12	networks	network	NOUN
ijassa-1239	87	13	neural	neural	ADJ
ijassa-1239	87	14	networks	network	NOUN
ijassa-1239	87	15	have	have	AUX
ijassa-1239	87	16	become	become	VERB
ijassa-1239	87	17	widespread	widespread	ADJ
ijassa-1239	87	18	due	due	ADP
ijassa-1239	87	19	to	to	ADP
ijassa-1239	87	20	the	the	DET
ijassa-1239	87	21	possibility	possibility	NOUN
ijassa-1239	87	22	of	of	ADP
ijassa-1239	87	23	their	their	PRON
ijassa-1239	87	24	application	application	NOUN
ijassa-1239	87	25	to	to	ADP
ijassa-1239	87	26	solving	solve	VERB
ijassa-1239	87	27	poorly	poorly	ADV
ijassa-1239	87	28	formalized	formalize	VERB
ijassa-1239	87	29	problems	problem	NOUN
ijassa-1239	87	30	.	.	PUNCT
ijassa-1239	88	1	in	in	ADP
ijassa-1239	88	2	addition	addition	NOUN
ijassa-1239	88	3	,	,	PUNCT
ijassa-1239	88	4	they	they	PRON
ijassa-1239	88	5	are	be	AUX
ijassa-1239	88	6	one	one	NUM
ijassa-1239	88	7	of	of	ADP
ijassa-1239	88	8	the	the	DET
ijassa-1239	88	9	main	main	ADJ
ijassa-1239	88	10	tools	tool	NOUN
ijassa-1239	88	11	for	for	ADP
ijassa-1239	88	12	big	big	ADJ
ijassa-1239	88	13	data	datum	NOUN
ijassa-1239	88	14	analysis	analysis	NOUN
ijassa-1239	88	15	.	.	PUNCT
ijassa-1239	89	1	it	it	PRON
ijassa-1239	89	2	is	be	AUX
ijassa-1239	89	3	currently	currently	ADV
ijassa-1239	89	4	difficult	difficult	ADJ
ijassa-1239	89	5	to	to	PART
ijassa-1239	89	6	name	name	VERB
ijassa-1239	89	7	an	an	DET
ijassa-1239	89	8	area	area	NOUN
ijassa-1239	89	9	in	in	ADP
ijassa-1239	89	10	which	which	PRON
ijassa-1239	89	11	neural	neural	ADJ
ijassa-1239	89	12	networks	network	NOUN
ijassa-1239	89	13	or	or	CCONJ
ijassa-1239	89	14	other	other	ADJ
ijassa-1239	89	15	machine	machine	NOUN
ijassa-1239	89	16	learning	learning	NOUN
ijassa-1239	89	17	methods	method	NOUN
ijassa-1239	89	18	would	would	AUX
ijassa-1239	89	19	not	not	PART
ijassa-1239	89	20	find	find	VERB
ijassa-1239	89	21	their	their	PRON
ijassa-1239	89	22	application	application	NOUN
ijassa-1239	89	23	.	.	PUNCT
ijassa-1239	90	1	the	the	DET
ijassa-1239	90	2	mathematical	mathematical	ADJ
ijassa-1239	90	3	model	model	NOUN
ijassa-1239	90	4	that	that	PRON
ijassa-1239	90	5	is	be	AUX
ijassa-1239	90	6	used	use	VERB
ijassa-1239	90	7	to	to	PART
ijassa-1239	90	8	describe	describe	VERB
ijassa-1239	90	9	the	the	DET
ijassa-1239	90	10	operation	operation	NOUN
ijassa-1239	90	11	of	of	ADP
ijassa-1239	90	12	a	a	DET
ijassa-1239	90	13	big	big	ADJ
ijassa-1239	90	14	data	datum	NOUN
ijassa-1239	90	15	processing	processing	NOUN
ijassa-1239	90	16	center	center	NOUN
ijassa-1239	90	17	is	be	AUX
ijassa-1239	90	18	a	a	DET
ijassa-1239	90	19	queuing	queue	VERB
ijassa-1239	90	20	system	system	NOUN
ijassa-1239	90	21	.	.	PUNCT
ijassa-1239	91	1	machine	machine	NOUN
ijassa-1239	91	2	learning	learn	VERB
ijassa-1239	91	3	methods	method	NOUN
ijassa-1239	91	4	and	and	CCONJ
ijassa-1239	91	5	neural	neural	ADJ
ijassa-1239	91	6	networks	network	NOUN
ijassa-1239	91	7	,	,	PUNCT
ijassa-1239	91	8	in	in	ADP
ijassa-1239	91	9	particular	particular	ADJ
ijassa-1239	91	10	,	,	PUNCT
ijassa-1239	91	11	have	have	AUX
ijassa-1239	91	12	been	be	AUX
ijassa-1239	91	13	applied	apply	VERB
ijassa-1239	91	14	to	to	ADP
ijassa-1239	91	15	solving	solve	VERB
ijassa-1239	91	16	complex	complex	ADJ
ijassa-1239	91	17	problems	problem	NOUN
ijassa-1239	91	18	of	of	ADP
ijassa-1239	91	19	queuing	queue	VERB
ijassa-1239	91	20	theory	theory	NOUN
ijassa-1239	91	21	relatively	relatively	ADV
ijassa-1239	91	22	recently	recently	ADV
ijassa-1239	91	23	,	,	PUNCT
ijassa-1239	91	24	although	although	SCONJ
ijassa-1239	91	25	this	this	DET
ijassa-1239	91	26	prospect	prospect	NOUN
ijassa-1239	91	27	was	be	AUX
ijassa-1239	91	28	predictable	predictable	ADJ
ijassa-1239	91	29	.	.	PUNCT
ijassa-1239	92	1	complex	complex	ADJ
ijassa-1239	92	2	problems	problem	NOUN
ijassa-1239	92	3	in	in	ADP
ijassa-1239	92	4	the	the	DET
ijassa-1239	92	5	field	field	NOUN
ijassa-1239	92	6	of	of	ADP
ijassa-1239	92	7	queuing	queue	VERB
ijassa-1239	92	8	theory	theory	NOUN
ijassa-1239	92	9	are	be	AUX
ijassa-1239	92	10	understood	understand	VERB
ijassa-1239	92	11	as	as	ADP
ijassa-1239	92	12	problems	problem	NOUN
ijassa-1239	92	13	that	that	PRON
ijassa-1239	92	14	can	can	AUX
ijassa-1239	92	15	not	not	PART
ijassa-1239	92	16	be	be	AUX
ijassa-1239	92	17	solved	solve	VERB
ijassa-1239	92	18	by	by	ADP
ijassa-1239	92	19	using	use	VERB
ijassa-1239	92	20	well	well	ADV
ijassa-1239	92	21	-	-	PUNCT
ijassa-1239	92	22	known	know	VERB
ijassa-1239	92	23	analytical	analytical	ADJ
ijassa-1239	92	24	methods	method	NOUN
ijassa-1239	92	25	,	,	PUNCT
ijassa-1239	92	26	or	or	CCONJ
ijassa-1239	92	27	the	the	DET
ijassa-1239	92	28	solution	solution	NOUN
ijassa-1239	92	29	is	be	AUX
ijassa-1239	92	30	so	so	ADV
ijassa-1239	92	31	complicated	complicated	ADJ
ijassa-1239	92	32	that	that	SCONJ
ijassa-1239	92	33	actually	actually	ADV
ijassa-1239	92	34	obtaining	obtain	VERB
ijassa-1239	92	35	numerical	numerical	ADJ
ijassa-1239	92	36	results	result	NOUN
ijassa-1239	92	37	using	use	VERB
ijassa-1239	92	38	the	the	DET
ijassa-1239	92	39	developed	develop	VERB
ijassa-1239	92	40	algorithms	algorithm	NOUN
ijassa-1239	92	41	is	be	AUX
ijassa-1239	92	42	difficult	difficult	ADJ
ijassa-1239	92	43	to	to	PART
ijassa-1239	92	44	implement	implement	VERB
ijassa-1239	92	45	even	even	ADV
ijassa-1239	92	46	taking	take	VERB
ijassa-1239	92	47	into	into	ADP
ijassa-1239	92	48	account	account	NOUN
ijassa-1239	92	49	the	the	DET
ijassa-1239	92	50	capabilities	capability	NOUN
ijassa-1239	92	51	of	of	ADP
ijassa-1239	92	52	modern	modern	ADJ
ijassa-1239	92	53	computers	computer	NOUN
ijassa-1239	92	54	.	.	PUNCT
ijassa-1239	93	1	an	an	DET
ijassa-1239	93	2	overview	overview	NOUN
ijassa-1239	93	3	of	of	ADP
ijassa-1239	93	4	publications	publication	NOUN
ijassa-1239	93	5	on	on	ADP
ijassa-1239	93	6	the	the	DET
ijassa-1239	93	7	application	application	NOUN
ijassa-1239	93	8	of	of	ADP
ijassa-1239	93	9	machine	machine	NOUN
ijassa-1239	93	10	learning	learn	VERB
ijassa-1239	93	11	methods	method	NOUN
ijassa-1239	93	12	to	to	ADP
ijassa-1239	93	13	solving	solve	VERB
ijassa-1239	93	14	problems	problem	NOUN
ijassa-1239	93	15	in	in	ADP
ijassa-1239	93	16	the	the	DET
ijassa-1239	93	17	field	field	NOUN
ijassa-1239	93	18	of	of	ADP
ijassa-1239	93	19	queuing	queue	VERB
ijassa-1239	93	20	theory	theory	NOUN
ijassa-1239	93	21	can	can	AUX
ijassa-1239	93	22	be	be	AUX
ijassa-1239	93	23	found	find	VERB
ijassa-1239	93	24	in	in	ADP
ijassa-1239	93	25	[	[	X
ijassa-1239	93	26	21	21	NUM
ijassa-1239	93	27	]	]	PUNCT
ijassa-1239	93	28	.	.	PUNCT
ijassa-1239	94	1	the	the	DET
ijassa-1239	94	2	idea	idea	NOUN
ijassa-1239	94	3	of	of	ADP
ijassa-1239	94	4	using	use	VERB
ijassa-1239	94	5	neural	neural	ADJ
ijassa-1239	94	6	networks	network	NOUN
ijassa-1239	94	7	is	be	AUX
ijassa-1239	94	8	based	base	VERB
ijassa-1239	94	9	on	on	ADP
ijassa-1239	94	10	the	the	DET
ijassa-1239	94	11	possibility	possibility	NOUN
ijassa-1239	94	12	of	of	ADP
ijassa-1239	94	13	using	use	VERB
ijassa-1239	94	14	them	they	PRON
ijassa-1239	94	15	to	to	PART
ijassa-1239	94	16	solve	solve	VERB
ijassa-1239	94	17	the	the	DET
ijassa-1239	94	18	problem	problem	NOUN
ijassa-1239	94	19	of	of	ADP
ijassa-1239	94	20	forecasting	forecasting	NOUN
ijassa-1239	94	21	or	or	CCONJ
ijassa-1239	94	22	,	,	PUNCT
ijassa-1239	94	23	in	in	ADP
ijassa-1239	94	24	fact	fact	NOUN
ijassa-1239	94	25	,	,	PUNCT
ijassa-1239	94	26	the	the	DET
ijassa-1239	94	27	problem	problem	NOUN
ijassa-1239	94	28	of	of	ADP
ijassa-1239	94	29	approximating	approximate	VERB
ijassa-1239	94	30	a	a	DET
ijassa-1239	94	31	function	function	NOUN
ijassa-1239	94	32	of	of	ADP
ijassa-1239	94	33	several	several	ADJ
ijassa-1239	94	34	variables	variable	NOUN
ijassa-1239	94	35	.	.	PUNCT
ijassa-1239	95	1	it	it	PRON
ijassa-1239	95	2	is	be	AUX
ijassa-1239	95	3	clear	clear	ADJ
ijassa-1239	95	4	that	that	SCONJ
ijassa-1239	95	5	the	the	DET
ijassa-1239	95	6	desired	desire	VERB
ijassa-1239	95	7	estimates	estimate	NOUN
ijassa-1239	95	8	of	of	ADP
ijassa-1239	95	9	the	the	DET
ijassa-1239	95	10	mean	mean	ADJ
ijassa-1239	95	11	response	response	NOUN
ijassa-1239	95	12	time	time	NOUN
ijassa-1239	95	13	and	and	CCONJ
ijassa-1239	95	14	its	its	PRON
ijassa-1239	95	15	tail	tail	NOUN
ijassa-1239	95	16	delay	delay	NOUN
ijassa-1239	95	17	depend	depend	VERB
ijassa-1239	95	18	,	,	PUNCT
ijassa-1239	95	19	for	for	ADP
ijassa-1239	95	20	example	example	NOUN
ijassa-1239	95	21	,	,	PUNCT
ijassa-1239	95	22	on	on	ADP
ijassa-1239	95	23	the	the	DET
ijassa-1239	95	24	values	value	NOUN
ijassa-1239	95	25	of	of	ADP
ijassa-1239	95	26	such	such	ADJ
ijassa-1239	95	27	parameters	parameter	NOUN
ijassa-1239	95	28	as	as	ADP
ijassa-1239	95	29	the	the	DET
ijassa-1239	95	30	system	system	NOUN
ijassa-1239	95	31	load	load	NOUN
ijassa-1239	95	32	,	,	PUNCT
ijassa-1239	95	33	the	the	DET
ijassa-1239	95	34	number	number	NOUN
ijassa-1239	95	35	of	of	ADP
ijassa-1239	95	36	subsystems	subsystem	NOUN
ijassa-1239	95	37	k	k	PROPN
ijassa-1239	95	38	and	and	CCONJ
ijassa-1239	95	39	servers	server	NOUN
ijassa-1239	95	40	in	in	ADP
ijassa-1239	95	41	them	they	PRON
ijassa-1239	95	42	,	,	PUNCT
ijassa-1239	95	43	the	the	DET
ijassa-1239	95	44	intensities	intensity	NOUN
ijassa-1239	95	45	for	for	ADP
ijassa-1239	95	46	the	the	DET
ijassa-1239	95	47	incoming	incoming	ADJ
ijassa-1239	95	48	flow	flow	NOUN
ijassa-1239	95	49	and	and	CCONJ
ijassa-1239	95	50	for	for	ADP
ijassa-1239	95	51	the	the	DET
ijassa-1239	95	52	servicing	servicing	NOUN
ijassa-1239	95	53	time	time	NOUN
ijassa-1239	95	54	on	on	ADP
ijassa-1239	95	55	the	the	DET
ijassa-1239	95	56	servers	server	NOUN
ijassa-1239	95	57	.	.	PUNCT
ijassa-1239	96	1	therefore	therefore	ADV
ijassa-1239	96	2	,	,	PUNCT
ijassa-1239	96	3	the	the	DET
ijassa-1239	96	4	problem	problem	NOUN
ijassa-1239	96	5	of	of	ADP
ijassa-1239	96	6	finding	find	VERB
ijassa-1239	96	7	estimates	estimate	NOUN
ijassa-1239	96	8	of	of	ADP
ijassa-1239	96	9	the	the	DET
ijassa-1239	96	10	response	response	NOUN
ijassa-1239	96	11	time	time	NOUN
ijassa-1239	96	12	can	can	AUX
ijassa-1239	96	13	be	be	AUX
ijassa-1239	96	14	considered	consider	VERB
ijassa-1239	96	15	as	as	ADP
ijassa-1239	96	16	a	a	DET
ijassa-1239	96	17	problem	problem	NOUN
ijassa-1239	96	18	of	of	ADP
ijassa-1239	96	19	approximating	approximate	VERB
ijassa-1239	96	20	a	a	DET
ijassa-1239	96	21	function	function	NOUN
ijassa-1239	96	22	depending	depend	VERB
ijassa-1239	96	23	on	on	ADP
ijassa-1239	96	24	the	the	DET
ijassa-1239	96	25	listed	list	VERB
ijassa-1239	96	26	parameters	parameter	NOUN
ijassa-1239	96	27	.	.	PUNCT
ijassa-1239	97	1	to	to	PART
ijassa-1239	97	2	interpolate	interpolate	VERB
ijassa-1239	97	3	a	a	DET
ijassa-1239	97	4	function	function	NOUN
ijassa-1239	97	5	,	,	PUNCT
ijassa-1239	97	6	a	a	DET
ijassa-1239	97	7	set	set	NOUN
ijassa-1239	97	8	of	of	ADP
ijassa-1239	97	9	values	value	NOUN
ijassa-1239	97	10	of	of	ADP
ijassa-1239	97	11	the	the	DET
ijassa-1239	97	12	input	input	NOUN
ijassa-1239	97	13	parameters	parameter	NOUN
ijassa-1239	97	14	and	and	CCONJ
ijassa-1239	97	15	the	the	DET
ijassa-1239	97	16	corresponding	corresponding	ADJ
ijassa-1239	97	17	true	true	ADJ
ijassa-1239	97	18	values	value	NOUN
ijassa-1239	97	19	of	of	ADP
ijassa-1239	97	20	the	the	DET
ijassa-1239	97	21	approximated	approximate	VERB
ijassa-1239	97	22	quantities	quantity	NOUN
ijassa-1239	97	23	are	be	AUX
ijassa-1239	97	24	required	require	VERB
ijassa-1239	97	25	.	.	PUNCT
ijassa-1239	98	1	there	there	PRON
ijassa-1239	98	2	are	be	VERB
ijassa-1239	98	3	several	several	ADJ
ijassa-1239	98	4	ways	way	NOUN
ijassa-1239	98	5	to	to	PART
ijassa-1239	98	6	get	get	VERB
ijassa-1239	98	7	the	the	DET
ijassa-1239	98	8	copyright	copyright	NOUN
ijassa-1239	98	9	©	©	ADP
ijassa-1239	98	10	2022	2022	NUM
ijassa-1239	98	11	assa	assa	NOUN
ijassa-1239	98	12	.	.	PUNCT
ijassa-1239	99	1	adv	adv	PROPN
ijassa-1239	99	2	syst	syst	PROPN
ijassa-1239	99	3	sci	sci	PROPN
ijassa-1239	99	4	appl	appl	PROPN
ijassa-1239	99	5	(	(	PUNCT
ijassa-1239	99	6	2022	2022	NUM
ijassa-1239	99	7	)	)	PUNCT
ijassa-1239	99	8	74	74	NUM
ijassa-1239	99	9	a.v	a.v	PROPN
ijassa-1239	99	10	.	.	PROPN
ijassa-1239	99	11	gorbunova	gorbunova	PROPN
ijassa-1239	99	12	,	,	PUNCT
ijassa-1239	99	13	v.m	v.m	PROPN
ijassa-1239	99	14	.	.	PUNCT
ijassa-1239	100	1	vishnevsky	vishnevsky	ADJ
ijassa-1239	100	2	true	true	ADJ
ijassa-1239	100	3	values	value	NOUN
ijassa-1239	100	4	.	.	PUNCT
ijassa-1239	101	1	for	for	ADP
ijassa-1239	101	2	example	example	NOUN
ijassa-1239	101	3	,	,	PUNCT
ijassa-1239	101	4	with	with	ADP
ijassa-1239	101	5	the	the	DET
ijassa-1239	101	6	help	help	NOUN
ijassa-1239	101	7	of	of	ADP
ijassa-1239	101	8	simulation	simulation	NOUN
ijassa-1239	101	9	modeling	modeling	NOUN
ijassa-1239	101	10	or	or	CCONJ
ijassa-1239	101	11	with	with	ADP
ijassa-1239	101	12	the	the	DET
ijassa-1239	101	13	help	help	NOUN
ijassa-1239	101	14	of	of	ADP
ijassa-1239	101	15	an	an	DET
ijassa-1239	101	16	exact	exact	ADJ
ijassa-1239	101	17	analytical	analytical	ADJ
ijassa-1239	101	18	solution	solution	NOUN
ijassa-1239	101	19	,	,	PUNCT
ijassa-1239	101	20	which	which	PRON
ijassa-1239	101	21	is	be	AUX
ijassa-1239	101	22	not	not	PART
ijassa-1239	101	23	available	available	ADJ
ijassa-1239	101	24	in	in	ADP
ijassa-1239	101	25	this	this	DET
ijassa-1239	101	26	case	case	NOUN
ijassa-1239	101	27	.	.	PUNCT
ijassa-1239	102	1	as	as	ADP
ijassa-1239	102	2	an	an	DET
ijassa-1239	102	3	alternative	alternative	NOUN
ijassa-1239	102	4	to	to	ADP
ijassa-1239	102	5	the	the	DET
ijassa-1239	102	6	exact	exact	ADJ
ijassa-1239	102	7	analytical	analytical	ADJ
ijassa-1239	102	8	solution	solution	NOUN
ijassa-1239	102	9	,	,	PUNCT
ijassa-1239	102	10	one	one	PRON
ijassa-1239	102	11	can	can	AUX
ijassa-1239	102	12	use	use	VERB
ijassa-1239	102	13	,	,	PUNCT
ijassa-1239	102	14	for	for	ADP
ijassa-1239	102	15	example	example	NOUN
ijassa-1239	102	16	,	,	PUNCT
ijassa-1239	102	17	the	the	DET
ijassa-1239	102	18	time	time	NOUN
ijassa-1239	102	19	-	-	PUNCT
ijassa-1239	102	20	consuming	consume	VERB
ijassa-1239	102	21	algorithm	algorithm	NOUN
ijassa-1239	102	22	proposed	propose	VERB
ijassa-1239	102	23	in	in	ADP
ijassa-1239	102	24	[	[	X
ijassa-1239	102	25	18	18	NUM
ijassa-1239	102	26	]	]	PUNCT
ijassa-1239	102	27	to	to	PART
ijassa-1239	102	28	obtain	obtain	VERB
ijassa-1239	102	29	tail	tail	NOUN
ijassa-1239	102	30	delays	delay	NOUN
ijassa-1239	102	31	in	in	ADP
ijassa-1239	102	32	the	the	DET
ijassa-1239	102	33	region	region	NOUN
ijassa-1239	102	34	where	where	SCONJ
ijassa-1239	102	35	a	a	DET
ijassa-1239	102	36	high	high	ADJ
ijassa-1239	102	37	-	-	PUNCT
ijassa-1239	102	38	precision	precision	NOUN
ijassa-1239	102	39	solution	solution	NOUN
ijassa-1239	102	40	exists	exist	VERB
ijassa-1239	102	41	.	.	PUNCT
ijassa-1239	103	1	the	the	DET
ijassa-1239	103	2	need	need	NOUN
ijassa-1239	103	3	to	to	PART
ijassa-1239	103	4	combine	combine	VERB
ijassa-1239	103	5	neural	neural	ADJ
ijassa-1239	103	6	networks	network	NOUN
ijassa-1239	103	7	with	with	ADP
ijassa-1239	103	8	simulation	simulation	NOUN
ijassa-1239	103	9	or	or	CCONJ
ijassa-1239	103	10	algorithmic	algorithmic	ADJ
ijassa-1239	103	11	solution	solution	NOUN
ijassa-1239	103	12	arises	arise	VERB
ijassa-1239	103	13	from	from	ADP
ijassa-1239	103	14	the	the	DET
ijassa-1239	103	15	significant	significant	ADJ
ijassa-1239	103	16	time	time	NOUN
ijassa-1239	103	17	costs	cost	NOUN
ijassa-1239	103	18	that	that	PRON
ijassa-1239	103	19	are	be	AUX
ijassa-1239	103	20	required	require	VERB
ijassa-1239	103	21	when	when	SCONJ
ijassa-1239	103	22	using	use	VERB
ijassa-1239	103	23	only	only	ADV
ijassa-1239	103	24	a	a	DET
ijassa-1239	103	25	simulation	simulation	NOUN
ijassa-1239	103	26	or	or	CCONJ
ijassa-1239	103	27	only	only	ADV
ijassa-1239	103	28	an	an	DET
ijassa-1239	103	29	algorithm	algorithm	NOUN
ijassa-1239	103	30	.	.	PUNCT
ijassa-1239	104	1	therefore	therefore	ADV
ijassa-1239	104	2	,	,	PUNCT
ijassa-1239	104	3	we	we	PRON
ijassa-1239	104	4	limit	limit	VERB
ijassa-1239	104	5	the	the	DET
ijassa-1239	104	6	amount	amount	NOUN
ijassa-1239	104	7	of	of	ADP
ijassa-1239	104	8	input	input	NOUN
ijassa-1239	104	9	data	datum	NOUN
ijassa-1239	104	10	for	for	ADP
ijassa-1239	104	11	which	which	PRON
ijassa-1239	104	12	it	it	PRON
ijassa-1239	104	13	is	be	AUX
ijassa-1239	104	14	necessary	necessary	ADJ
ijassa-1239	104	15	to	to	PART
ijassa-1239	104	16	use	use	VERB
ijassa-1239	104	17	simulation	simulation	NOUN
ijassa-1239	104	18	modeling	modeling	NOUN
ijassa-1239	104	19	or	or	CCONJ
ijassa-1239	104	20	a	a	DET
ijassa-1239	104	21	computational	computational	ADJ
ijassa-1239	104	22	algorithm	algorithm	NOUN
ijassa-1239	104	23	.	.	PUNCT
ijassa-1239	105	1	then	then	ADV
ijassa-1239	105	2	,	,	PUNCT
ijassa-1239	105	3	on	on	ADP
ijassa-1239	105	4	the	the	DET
ijassa-1239	105	5	resulting	result	VERB
ijassa-1239	105	6	set	set	NOUN
ijassa-1239	105	7	,	,	PUNCT
ijassa-1239	105	8	we	we	PRON
ijassa-1239	105	9	train	train	VERB
ijassa-1239	105	10	the	the	DET
ijassa-1239	105	11	neural	neural	ADJ
ijassa-1239	105	12	network	network	NOUN
ijassa-1239	105	13	,	,	PUNCT
ijassa-1239	105	14	which	which	PRON
ijassa-1239	105	15	will	will	AUX
ijassa-1239	105	16	allow	allow	VERB
ijassa-1239	105	17	us	we	PRON
ijassa-1239	105	18	to	to	PART
ijassa-1239	105	19	predict	predict	VERB
ijassa-1239	105	20	the	the	DET
ijassa-1239	105	21	characteristics	characteristic	NOUN
ijassa-1239	105	22	for	for	ADP
ijassa-1239	105	23	any	any	DET
ijassa-1239	105	24	intermediate	intermediate	ADJ
ijassa-1239	105	25	values	value	NOUN
ijassa-1239	105	26	of	of	ADP
ijassa-1239	105	27	input	input	NOUN
ijassa-1239	105	28	parameters	parameter	NOUN
ijassa-1239	105	29	without	without	ADP
ijassa-1239	105	30	restrictions	restriction	NOUN
ijassa-1239	105	31	on	on	ADP
ijassa-1239	105	32	their	their	PRON
ijassa-1239	105	33	number	number	NOUN
ijassa-1239	105	34	in	in	ADP
ijassa-1239	105	35	the	the	DET
ijassa-1239	105	36	minimum	minimum	ADJ
ijassa-1239	105	37	time	time	NOUN
ijassa-1239	105	38	comparable	comparable	ADJ
ijassa-1239	105	39	to	to	ADP
ijassa-1239	105	40	the	the	DET
ijassa-1239	105	41	time	time	NOUN
ijassa-1239	105	42	required	require	VERB
ijassa-1239	105	43	for	for	ADP
ijassa-1239	105	44	calculations	calculation	NOUN
ijassa-1239	105	45	using	use	VERB
ijassa-1239	105	46	a	a	DET
ijassa-1239	105	47	simple	simple	ADJ
ijassa-1239	105	48	analytical	analytical	ADJ
ijassa-1239	105	49	formula	formula	NOUN
ijassa-1239	105	50	.	.	PUNCT
ijassa-1239	106	1	for	for	ADP
ijassa-1239	106	2	clarity	clarity	NOUN
ijassa-1239	106	3	,	,	PUNCT
ijassa-1239	106	4	we	we	PRON
ijassa-1239	106	5	describe	describe	VERB
ijassa-1239	106	6	the	the	DET
ijassa-1239	106	7	main	main	ADJ
ijassa-1239	106	8	stages	stage	NOUN
ijassa-1239	106	9	of	of	ADP
ijassa-1239	106	10	the	the	DET
ijassa-1239	106	11	proposed	propose	VERB
ijassa-1239	106	12	method	method	NOUN
ijassa-1239	106	13	:	:	PUNCT
ijassa-1239	106	14	1	1	X
ijassa-1239	106	15	.	.	X
ijassa-1239	106	16	obtaining	obtain	VERB
ijassa-1239	106	17	by	by	ADP
ijassa-1239	106	18	means	mean	NOUN
ijassa-1239	106	19	of	of	ADP
ijassa-1239	106	20	simulation	simulation	NOUN
ijassa-1239	106	21	modeling	modeling	NOUN
ijassa-1239	106	22	or	or	CCONJ
ijassa-1239	106	23	a	a	DET
ijassa-1239	106	24	labor	labor	NOUN
ijassa-1239	106	25	-	-	PUNCT
ijassa-1239	106	26	intensive	intensive	ADJ
ijassa-1239	106	27	computational	computational	ADJ
ijassa-1239	106	28	algorithm	algorithm	NOUN
ijassa-1239	106	29	the	the	DET
ijassa-1239	106	30	values	value	NOUN
ijassa-1239	106	31	of	of	ADP
ijassa-1239	106	32	the	the	DET
ijassa-1239	106	33	characteristics	characteristic	NOUN
ijassa-1239	106	34	of	of	ADP
ijassa-1239	106	35	the	the	DET
ijassa-1239	106	36	analyzed	analyze	VERB
ijassa-1239	106	37	system	system	NOUN
ijassa-1239	106	38	of	of	ADP
ijassa-1239	106	39	interest	interest	NOUN
ijassa-1239	106	40	for	for	ADP
ijassa-1239	106	41	a	a	DET
ijassa-1239	106	42	finite	finite	ADJ
ijassa-1239	106	43	set	set	NOUN
ijassa-1239	106	44	of	of	ADP
ijassa-1239	106	45	values	value	NOUN
ijassa-1239	106	46	from	from	ADP
ijassa-1239	106	47	the	the	DET
ijassa-1239	106	48	given	give	VERB
ijassa-1239	106	49	numerical	numerical	ADJ
ijassa-1239	106	50	intervals	interval	NOUN
ijassa-1239	106	51	for	for	ADP
ijassa-1239	106	52	the	the	DET
ijassa-1239	106	53	input	input	NOUN
ijassa-1239	106	54	parameters	parameter	NOUN
ijassa-1239	106	55	on	on	ADP
ijassa-1239	106	56	which	which	PRON
ijassa-1239	106	57	the	the	DET
ijassa-1239	106	58	performance	performance	NOUN
ijassa-1239	106	59	of	of	ADP
ijassa-1239	106	60	the	the	DET
ijassa-1239	106	61	system	system	NOUN
ijassa-1239	106	62	depends	depend	VERB
ijassa-1239	106	63	;	;	PUNCT
ijassa-1239	106	64	2	2	X
ijassa-1239	106	65	.	.	X
ijassa-1239	106	66	training	train	VERB
ijassa-1239	106	67	an	an	DET
ijassa-1239	106	68	intellectual	intellectual	ADJ
ijassa-1239	106	69	model	model	NOUN
ijassa-1239	106	70	on	on	ADP
ijassa-1239	106	71	the	the	DET
ijassa-1239	106	72	data	datum	NOUN
ijassa-1239	106	73	obtained	obtain	VERB
ijassa-1239	106	74	using	use	VERB
ijassa-1239	106	75	simulation	simulation	NOUN
ijassa-1239	106	76	by	by	ADP
ijassa-1239	106	77	one	one	NUM
ijassa-1239	106	78	of	of	ADP
ijassa-1239	106	79	the	the	DET
ijassa-1239	106	80	machine	machine	NOUN
ijassa-1239	106	81	learning	learn	VERB
ijassa-1239	106	82	methods	method	NOUN
ijassa-1239	106	83	in	in	ADP
ijassa-1239	106	84	order	order	NOUN
ijassa-1239	106	85	to	to	PART
ijassa-1239	106	86	solve	solve	VERB
ijassa-1239	106	87	the	the	DET
ijassa-1239	106	88	forecasting	forecasting	NOUN
ijassa-1239	106	89	problem	problem	NOUN
ijassa-1239	106	90	;	;	PUNCT
ijassa-1239	106	91	3	3	X
ijassa-1239	106	92	.	.	X
ijassa-1239	106	93	almost	almost	ADV
ijassa-1239	106	94	instantaneous	instantaneous	ADJ
ijassa-1239	106	95	assessment	assessment	NOUN
ijassa-1239	106	96	of	of	ADP
ijassa-1239	106	97	the	the	DET
ijassa-1239	106	98	desired	desire	VERB
ijassa-1239	106	99	performance	performance	NOUN
ijassa-1239	106	100	characteristics	characteristic	NOUN
ijassa-1239	106	101	for	for	ADP
ijassa-1239	106	102	any	any	DET
ijassa-1239	106	103	other	other	ADJ
ijassa-1239	106	104	intermediate	intermediate	ADJ
ijassa-1239	106	105	values	value	NOUN
ijassa-1239	106	106	of	of	ADP
ijassa-1239	106	107	input	input	NOUN
ijassa-1239	106	108	parameters	parameter	NOUN
ijassa-1239	106	109	on	on	ADP
ijassa-1239	106	110	the	the	DET
ijassa-1239	106	111	same	same	ADJ
ijassa-1239	106	112	numerical	numerical	ADJ
ijassa-1239	106	113	intervals	interval	NOUN
ijassa-1239	106	114	using	use	VERB
ijassa-1239	106	115	a	a	DET
ijassa-1239	106	116	trained	train	VERB
ijassa-1239	106	117	intelligent	intelligent	ADJ
ijassa-1239	106	118	model	model	NOUN
ijassa-1239	106	119	.	.	PUNCT
ijassa-1239	107	1	among	among	ADP
ijassa-1239	107	2	the	the	DET
ijassa-1239	107	3	main	main	ADJ
ijassa-1239	107	4	advantages	advantage	NOUN
ijassa-1239	107	5	of	of	ADP
ijassa-1239	107	6	the	the	DET
ijassa-1239	107	7	described	describe	VERB
ijassa-1239	107	8	technique	technique	NOUN
ijassa-1239	107	9	,	,	PUNCT
ijassa-1239	107	10	universality	universality	NOUN
ijassa-1239	107	11	can	can	AUX
ijassa-1239	107	12	be	be	AUX
ijassa-1239	107	13	distinguished	distinguish	VERB
ijassa-1239	107	14	,	,	PUNCT
ijassa-1239	107	15	since	since	SCONJ
ijassa-1239	107	16	a	a	DET
ijassa-1239	107	17	simulation	simulation	NOUN
ijassa-1239	107	18	modeling	modeling	NOUN
ijassa-1239	107	19	is	be	AUX
ijassa-1239	107	20	sometimes	sometimes	ADV
ijassa-1239	107	21	the	the	DET
ijassa-1239	107	22	the	the	DET
ijassa-1239	107	23	only	only	ADJ
ijassa-1239	107	24	possible	possible	ADJ
ijassa-1239	107	25	way	way	NOUN
ijassa-1239	107	26	to	to	PART
ijassa-1239	107	27	analyze	analyze	VERB
ijassa-1239	107	28	complex	complex	ADJ
ijassa-1239	107	29	systems	system	NOUN
ijassa-1239	107	30	.	.	PUNCT
ijassa-1239	108	1	however	however	ADV
ijassa-1239	108	2	,	,	PUNCT
ijassa-1239	108	3	it	it	PRON
ijassa-1239	108	4	is	be	AUX
ijassa-1239	108	5	a	a	DET
ijassa-1239	108	6	resource	resource	NOUN
ijassa-1239	108	7	-	-	PUNCT
ijassa-1239	108	8	intensive	intensive	ADJ
ijassa-1239	108	9	tool	tool	NOUN
ijassa-1239	108	10	.	.	PUNCT
ijassa-1239	109	1	thanks	thank	NOUN
ijassa-1239	109	2	to	to	ADP
ijassa-1239	109	3	the	the	DET
ijassa-1239	109	4	use	use	NOUN
ijassa-1239	109	5	of	of	ADP
ijassa-1239	109	6	neural	neural	ADJ
ijassa-1239	109	7	networks	network	NOUN
ijassa-1239	109	8	,	,	PUNCT
ijassa-1239	109	9	this	this	DET
ijassa-1239	109	10	disadvantage	disadvantage	NOUN
ijassa-1239	109	11	can	can	AUX
ijassa-1239	109	12	be	be	AUX
ijassa-1239	109	13	eliminated	eliminate	VERB
ijassa-1239	109	14	.	.	PUNCT
ijassa-1239	110	1	4	4	X
ijassa-1239	110	2	.	.	X
ijassa-1239	110	3	mathematical	mathematical	ADJ
ijassa-1239	110	4	model	model	NOUN
ijassa-1239	110	5	of	of	ADP
ijassa-1239	110	6	the	the	DET
ijassa-1239	110	7	parallel	parallel	ADJ
ijassa-1239	110	8	structure	structure	NOUN
ijassa-1239	110	9	of	of	ADP
ijassa-1239	110	10	the	the	DET
ijassa-1239	110	11	big	big	ADJ
ijassa-1239	110	12	data	datum	NOUN
ijassa-1239	110	13	processing	processing	NOUN
ijassa-1239	110	14	center	center	NOUN
ijassa-1239	110	15	let	let	VERB
ijassa-1239	110	16	us	we	PRON
ijassa-1239	110	17	describe	describe	VERB
ijassa-1239	110	18	in	in	ADP
ijassa-1239	110	19	more	more	ADJ
ijassa-1239	110	20	detail	detail	NOUN
ijassa-1239	110	21	the	the	DET
ijassa-1239	110	22	architecture	architecture	NOUN
ijassa-1239	110	23	of	of	ADP
ijassa-1239	110	24	the	the	DET
ijassa-1239	110	25	fork	fork	NOUN
ijassa-1239	110	26	-	-	PUNCT
ijassa-1239	110	27	join	join	NOUN
ijassa-1239	110	28	qs	qs	NOUN
ijassa-1239	110	29	,	,	PUNCT
ijassa-1239	110	30	which	which	PRON
ijassa-1239	110	31	we	we	PRON
ijassa-1239	110	32	will	will	AUX
ijassa-1239	110	33	use	use	VERB
ijassa-1239	110	34	to	to	PART
ijassa-1239	110	35	model	model	VERB
ijassa-1239	110	36	the	the	DET
ijassa-1239	110	37	operation	operation	NOUN
ijassa-1239	110	38	of	of	ADP
ijassa-1239	110	39	a	a	DET
ijassa-1239	110	40	data	data	NOUN
ijassa-1239	110	41	center	center	NOUN
ijassa-1239	110	42	.	.	PUNCT
ijassa-1239	111	1	the	the	DET
ijassa-1239	111	2	system	system	NOUN
ijassa-1239	111	3	consists	consist	VERB
ijassa-1239	111	4	of	of	ADP
ijassa-1239	111	5	k	k	PROPN
ijassa-1239	111	6	subsystems	subsystem	NOUN
ijassa-1239	111	7	of	of	ADP
ijassa-1239	111	8	type	type	NOUN
ijassa-1239	111	9	g|g|n	g|g|n	PROPN
ijassa-1239	111	10	(	(	PUNCT
ijassa-1239	111	11	fig.4.2	fig.4.2	PROPN
ijassa-1239	111	12	)	)	PUNCT
ijassa-1239	111	13	.	.	PUNCT
ijassa-1239	112	1	a	a	DET
ijassa-1239	112	2	request	request	NOUN
ijassa-1239	112	3	entering	enter	VERB
ijassa-1239	112	4	the	the	DET
ijassa-1239	112	5	system	system	NOUN
ijassa-1239	112	6	is	be	AUX
ijassa-1239	112	7	split	split	VERB
ijassa-1239	112	8	into	into	ADP
ijassa-1239	112	9	k	k	PROPN
ijassa-1239	112	10	subtasks	subtask	NOUN
ijassa-1239	112	11	,	,	PUNCT
ijassa-1239	112	12	each	each	PRON
ijassa-1239	112	13	of	of	ADP
ijassa-1239	112	14	which	which	PRON
ijassa-1239	112	15	is	be	AUX
ijassa-1239	112	16	queued	queue	VERB
ijassa-1239	112	17	in	in	ADP
ijassa-1239	112	18	the	the	DET
ijassa-1239	112	19	corresponding	corresponding	ADJ
ijassa-1239	112	20	subsystem	subsystem	NOUN
ijassa-1239	112	21	.	.	PUNCT
ijassa-1239	113	1	servicing	servicing	NOUN
ijassa-1239	113	2	in	in	ADP
ijassa-1239	113	3	subsystems	subsystem	NOUN
ijassa-1239	113	4	occurs	occur	VERB
ijassa-1239	113	5	in	in	ADP
ijassa-1239	113	6	the	the	DET
ijassa-1239	113	7	order	order	NOUN
ijassa-1239	113	8	of	of	ADP
ijassa-1239	113	9	receipt	receipt	NOUN
ijassa-1239	113	10	of	of	ADP
ijassa-1239	113	11	subtasks	subtask	NOUN
ijassa-1239	113	12	(	(	PUNCT
ijassa-1239	113	13	first	first	ADV
ijassa-1239	113	14	in	in	ADP
ijassa-1239	113	15	first	first	ADV
ijassa-1239	113	16	out	out	ADV
ijassa-1239	113	17	,	,	PUNCT
ijassa-1239	113	18	fifo	fifo	ADJ
ijassa-1239	113	19	discipline	discipline	NOUN
ijassa-1239	113	20	)	)	PUNCT
ijassa-1239	113	21	.	.	PUNCT
ijassa-1239	114	1	each	each	DET
ijassa-1239	114	2	subsystem	subsystem	NOUN
ijassa-1239	114	3	contains	contain	VERB
ijassa-1239	114	4	the	the	DET
ijassa-1239	114	5	same	same	ADJ
ijassa-1239	114	6	number	number	NOUN
ijassa-1239	114	7	of	of	ADP
ijassa-1239	114	8	servers	server	NOUN
ijassa-1239	114	9	n	n	CCONJ
ijassa-1239	114	10	,	,	PUNCT
ijassa-1239	114	11	n	n	CCONJ
ijassa-1239	114	12	⩾	⩾	NOUN
ijassa-1239	114	13	1	1	X
ijassa-1239	114	14	.	.	X
ijassa-1239	114	15	selecting	select	VERB
ijassa-1239	114	16	a	a	DET
ijassa-1239	114	17	multiline	multiline	ADJ
ijassa-1239	114	18	system	system	NOUN
ijassa-1239	114	19	will	will	AUX
ijassa-1239	114	20	allow	allow	VERB
ijassa-1239	114	21	you	you	PRON
ijassa-1239	114	22	to	to	PART
ijassa-1239	114	23	analyze	analyze	VERB
ijassa-1239	114	24	the	the	DET
ijassa-1239	114	25	performance	performance	NOUN
ijassa-1239	114	26	improvement	improvement	NOUN
ijassa-1239	114	27	of	of	ADP
ijassa-1239	114	28	nodes	node	NOUN
ijassa-1239	114	29	by	by	ADP
ijassa-1239	114	30	provisioning	provision	VERB
ijassa-1239	114	31	additional	additional	ADJ
ijassa-1239	114	32	resources	resource	NOUN
ijassa-1239	114	33	,	,	PUNCT
ijassa-1239	114	34	as	as	SCONJ
ijassa-1239	114	35	additional	additional	ADJ
ijassa-1239	114	36	server	server	NOUN
ijassa-1239	114	37	replicas	replica	NOUN
ijassa-1239	114	38	are	be	AUX
ijassa-1239	114	39	modeled	model	VERB
ijassa-1239	114	40	in	in	ADP
ijassa-1239	114	41	this	this	DET
ijassa-1239	114	42	way	way	NOUN
ijassa-1239	114	43	.	.	PUNCT
ijassa-1239	115	1	based	base	VERB
ijassa-1239	115	2	on	on	ADP
ijassa-1239	115	3	the	the	DET
ijassa-1239	115	4	results	result	NOUN
ijassa-1239	115	5	of	of	ADP
ijassa-1239	115	6	the	the	DET
ijassa-1239	115	7	[	[	X
ijassa-1239	115	8	15	15	NUM
ijassa-1239	115	9	]	]	X
ijassa-1239	115	10	study	study	NOUN
ijassa-1239	115	11	,	,	PUNCT
ijassa-1239	115	12	we	we	PRON
ijassa-1239	115	13	will	will	AUX
ijassa-1239	115	14	restrict	restrict	VERB
ijassa-1239	115	15	ourselves	ourselves	PRON
ijassa-1239	115	16	to	to	ADP
ijassa-1239	115	17	the	the	DET
ijassa-1239	115	18	case	case	NOUN
ijassa-1239	115	19	with	with	ADP
ijassa-1239	115	20	3	3	NUM
ijassa-1239	115	21	server	server	NOUN
ijassa-1239	115	22	replicas	replica	NOUN
ijassa-1239	115	23	,	,	PUNCT
ijassa-1239	115	24	i.e.	i.e.	X
ijassa-1239	115	25	we	we	PRON
ijassa-1239	115	26	will	will	AUX
ijassa-1239	115	27	check	check	VERB
ijassa-1239	115	28	the	the	DET
ijassa-1239	115	29	accuracy	accuracy	NOUN
ijassa-1239	115	30	of	of	ADP
ijassa-1239	115	31	the	the	DET
ijassa-1239	115	32	proposed	propose	VERB
ijassa-1239	115	33	approach	approach	NOUN
ijassa-1239	115	34	for	for	ADP
ijassa-1239	115	35	1	1	NUM
ijassa-1239	115	36	⩽	⩽	NOUN
ijassa-1239	115	37	n	n	CCONJ
ijassa-1239	115	38	⩽	⩽	NOUN
ijassa-1239	115	39	3	3	X
ijassa-1239	115	40	.	.	PUNCT
ijassa-1239	116	1	as	as	ADP
ijassa-1239	116	2	a	a	DET
ijassa-1239	116	3	service	service	NOUN
ijassa-1239	116	4	time	time	NOUN
ijassa-1239	116	5	distribution	distribution	NOUN
ijassa-1239	116	6	we	we	PRON
ijassa-1239	116	7	will	will	AUX
ijassa-1239	116	8	consider	consider	VERB
ijassa-1239	116	9	a	a	DET
ijassa-1239	116	10	truncated	truncated	ADJ
ijassa-1239	116	11	pareto	pareto	ADJ
ijassa-1239	116	12	distribution	distribution	NOUN
ijassa-1239	116	13	with	with	ADP
ijassa-1239	116	14	a	a	DET
ijassa-1239	116	15	distribution	distribution	NOUN
ijassa-1239	116	16	function	function	NOUN
ijassa-1239	116	17	and	and	CCONJ
ijassa-1239	116	18	density	density	NOUN
ijassa-1239	116	19	of	of	ADP
ijassa-1239	116	20	the	the	DET
ijassa-1239	116	21	form	form	NOUN
ijassa-1239	116	22	[	[	X
ijassa-1239	116	23	4	4	NUM
ijassa-1239	116	24	]	]	PUNCT
ijassa-1239	116	25	:	:	PUNCT
ijassa-1239	116	26	f	f	X
ijassa-1239	116	27	(	(	PUNCT
ijassa-1239	116	28	x	x	X
ijassa-1239	116	29	)	)	PUNCT
ijassa-1239	116	30	=	=	SYM
ijassa-1239	116	31	1−	1−	NUM
ijassa-1239	116	32	(	(	PUNCT
ijassa-1239	116	33	l	l	NOUN
ijassa-1239	116	34	/	/	SYM
ijassa-1239	116	35	x)α	x)α	X
ijassa-1239	116	36	1−	1−	NUM
ijassa-1239	116	37	(	(	PUNCT
ijassa-1239	116	38	l	l	NOUN
ijassa-1239	116	39	/	/	SYM
ijassa-1239	116	40	h)α	h)α	ADJ
ijassa-1239	116	41	,	,	PUNCT
ijassa-1239	116	42	f(x	f(x	PROPN
ijassa-1239	116	43	)	)	PUNCT
ijassa-1239	116	44	=	=	PUNCT
ijassa-1239	117	1	αlαx−α−1	αlαx−α−1	NUM
ijassa-1239	117	2	1−	1−	NUM
ijassa-1239	117	3	(	(	PUNCT
ijassa-1239	117	4	l	l	NOUN
ijassa-1239	117	5	/	/	SYM
ijassa-1239	117	6	h)α	h)α	ADJ
ijassa-1239	117	7	,	,	PUNCT
ijassa-1239	117	8	0	0	NUM
ijassa-1239	117	9	⩽	⩽	NOUN
ijassa-1239	117	10	l	l	PROPN
ijassa-1239	117	11	⩽	⩽	PROPN
ijassa-1239	117	12	x	x	SYM
ijassa-1239	117	13	⩽	⩽	ADJ
ijassa-1239	117	14	h	h	PROPN
ijassa-1239	117	15	,	,	PUNCT
ijassa-1239	117	16	α	α	PROPN
ijassa-1239	117	17	>	>	X
ijassa-1239	117	18	0	0	PROPN
ijassa-1239	117	19	.	.	PUNCT
ijassa-1239	118	1	the	the	DET
ijassa-1239	118	2	truncated	truncated	ADJ
ijassa-1239	118	3	pareto	pareto	ADJ
ijassa-1239	118	4	distribution	distribution	NOUN
ijassa-1239	118	5	is	be	AUX
ijassa-1239	118	6	a	a	DET
ijassa-1239	118	7	three	three	NUM
ijassa-1239	118	8	-	-	PUNCT
ijassa-1239	118	9	parameter	parameter	NOUN
ijassa-1239	118	10	distribution	distribution	NOUN
ijassa-1239	118	11	.	.	PUNCT
ijassa-1239	119	1	the	the	DET
ijassa-1239	119	2	parameter	parameter	NOUN
ijassa-1239	119	3	α	α	PROPN
ijassa-1239	119	4	is	be	AUX
ijassa-1239	119	5	a	a	DET
ijassa-1239	119	6	shape	shape	NOUN
ijassa-1239	119	7	parameter	parameter	NOUN
ijassa-1239	119	8	,	,	PUNCT
ijassa-1239	119	9	and	and	CCONJ
ijassa-1239	119	10	the	the	DET
ijassa-1239	119	11	parameters	parameter	NOUN
ijassa-1239	119	12	l	l	PROPN
ijassa-1239	119	13	and	and	CCONJ
ijassa-1239	119	14	h	h	NOUN
ijassa-1239	119	15	are	be	AUX
ijassa-1239	119	16	in	in	ADP
ijassa-1239	119	17	fact	fact	NOUN
ijassa-1239	119	18	the	the	DET
ijassa-1239	119	19	minimum	minimum	ADJ
ijassa-1239	119	20	and	and	CCONJ
ijassa-1239	119	21	maximum	maximum	ADJ
ijassa-1239	119	22	values	value	NOUN
ijassa-1239	119	23	of	of	ADP
ijassa-1239	119	24	a	a	DET
ijassa-1239	119	25	random	random	ADJ
ijassa-1239	119	26	variable	variable	NOUN
ijassa-1239	119	27	with	with	ADP
ijassa-1239	119	28	a	a	DET
ijassa-1239	119	29	given	give	VERB
ijassa-1239	119	30	distribution	distribution	NOUN
ijassa-1239	119	31	.	.	PUNCT
ijassa-1239	120	1	in	in	ADP
ijassa-1239	120	2	[	[	X
ijassa-1239	120	3	15	15	NUM
ijassa-1239	120	4	]	]	PUNCT
ijassa-1239	120	5	,	,	PUNCT
ijassa-1239	120	6	based	base	VERB
ijassa-1239	120	7	on	on	ADP
ijassa-1239	120	8	empirical	empirical	ADJ
ijassa-1239	120	9	data	datum	NOUN
ijassa-1239	120	10	for	for	ADP
ijassa-1239	120	11	the	the	DET
ijassa-1239	120	12	google	google	NOUN
ijassa-1239	120	13	system	system	NOUN
ijassa-1239	120	14	from	from	ADP
ijassa-1239	120	15	[	[	X
ijassa-1239	120	16	12	12	NUM
ijassa-1239	120	17	]	]	PUNCT
ijassa-1239	120	18	,	,	PUNCT
ijassa-1239	120	19	the	the	DET
ijassa-1239	120	20	following	follow	VERB
ijassa-1239	120	21	values	value	NOUN
ijassa-1239	120	22	for	for	ADP
ijassa-1239	120	23	parameters	parameter	NOUN
ijassa-1239	120	24	of	of	ADP
ijassa-1239	120	25	service	service	NOUN
ijassa-1239	120	26	time	time	NOUN
ijassa-1239	120	27	distribution	distribution	NOUN
ijassa-1239	120	28	are	be	AUX
ijassa-1239	120	29	proposed	propose	VERB
ijassa-1239	120	30	:	:	PUNCT
ijassa-1239	120	31	α	α	X
ijassa-1239	120	32	=	=	SYM
ijassa-1239	120	33	2.0119	2.0119	NUM
ijassa-1239	120	34	,	,	PUNCT
ijassa-1239	120	35	l	l	NOUN
ijassa-1239	120	36	=	=	SYM
ijassa-1239	120	37	2.14	2.14	NUM
ijassa-1239	120	38	,	,	PUNCT
ijassa-1239	120	39	h	h	NOUN
ijassa-1239	120	40	=	=	NOUN
ijassa-1239	120	41	276.6	276.6	NUM
ijassa-1239	120	42	,	,	PUNCT
ijassa-1239	120	43	(	(	PUNCT
ijassa-1239	120	44	4.1	4.1	NUM
ijassa-1239	120	45	)	)	PUNCT
ijassa-1239	120	46	copyright	copyright	NOUN
ijassa-1239	120	47	©	©	PROPN
ijassa-1239	120	48	2022	2022	NUM
ijassa-1239	120	49	assa	assa	NOUN
ijassa-1239	120	50	.	.	PUNCT
ijassa-1239	121	1	adv	adv	PROPN
ijassa-1239	121	2	syst	syst	PROPN
ijassa-1239	121	3	sci	sci	PROPN
ijassa-1239	121	4	appl	appl	PROPN
ijassa-1239	121	5	(	(	PUNCT
ijassa-1239	121	6	2022	2022	NUM
ijassa-1239	121	7	)	)	PUNCT
ijassa-1239	121	8	the	the	DET
ijassa-1239	121	9	analysis	analysis	NOUN
ijassa-1239	121	10	of	of	ADP
ijassa-1239	121	11	big	big	ADJ
ijassa-1239	121	12	data	datum	NOUN
ijassa-1239	121	13	centers	center	NOUN
ijassa-1239	121	14	performance	performance	NOUN
ijassa-1239	121	15	75	75	NUM
ijassa-1239	121	16	...	...	PUNCT
ijassa-1239	121	17	.	.	PUNCT
ijassa-1239	121	18	.	.	PUNCT
ijassa-1239	121	19	.	.	PUNCT
ijassa-1239	122	1	fork	fork	PROPN
ijassa-1239	122	2	point	point	NOUN
ijassa-1239	122	3	join	join	VERB
ijassa-1239	122	4	point	point	NOUN
ijassa-1239	122	5	n	n	PRON
ijassa-1239	122	6	1	1	NUM
ijassa-1239	122	7	...	...	SYM
ijassa-1239	122	8	1	1	NUM
ijassa-1239	122	9	...	...	SYM
ijassa-1239	122	10	n	n	PRON
ijassa-1239	122	11	1	1	NUM
ijassa-1239	122	12	...	...	PUNCT
ijassa-1239	122	13	n	n	X
ijassa-1239	122	14	...	...	PUNCT
ijassa-1239	123	1	...	...	PUNCT
ijassa-1239	123	2	fig	fig	NOUN
ijassa-1239	123	3	.	.	PUNCT
ijassa-1239	124	1	4.2	4.2	NUM
ijassa-1239	124	2	.	.	PUNCT
ijassa-1239	124	3	fork	fork	NOUN
ijassa-1239	124	4	-	-	PUNCT
ijassa-1239	124	5	join	join	NOUN
ijassa-1239	124	6	model	model	NOUN
ijassa-1239	124	7	of	of	ADP
ijassa-1239	124	8	qs	qs	PROPN
ijassa-1239	124	9	with	with	ADP
ijassa-1239	124	10	subsystems	subsystem	NOUN
ijassa-1239	124	11	of	of	ADP
ijassa-1239	124	12	type	type	NOUN
ijassa-1239	124	13	g|g|n	g|g|n	PROPN
ijassa-1239	124	14	.	.	PUNCT
ijassa-1239	125	1	i.e.	i.e.	X
ijassa-1239	125	2	the	the	DET
ijassa-1239	125	3	minimum	minimum	ADJ
ijassa-1239	125	4	service	service	NOUN
ijassa-1239	125	5	time	time	NOUN
ijassa-1239	125	6	is	be	AUX
ijassa-1239	125	7	2.14	2.14	NUM
ijassa-1239	125	8	ms	ms	NOUN
ijassa-1239	125	9	,	,	PUNCT
ijassa-1239	125	10	and	and	CCONJ
ijassa-1239	125	11	the	the	DET
ijassa-1239	125	12	maximum	maximum	NOUN
ijassa-1239	125	13	is	be	AUX
ijassa-1239	125	14	276.6	276.6	NUM
ijassa-1239	125	15	ms	ms	PROPN
ijassa-1239	125	16	.	.	PUNCT
ijassa-1239	126	1	the	the	DET
ijassa-1239	126	2	k	k	NOUN
ijassa-1239	126	3	-	-	PUNCT
ijassa-1239	126	4	th	th	VERB
ijassa-1239	126	5	moment	moment	NOUN
ijassa-1239	126	6	of	of	ADP
ijassa-1239	126	7	the	the	DET
ijassa-1239	126	8	truncated	truncated	ADJ
ijassa-1239	126	9	pareto	pareto	ADJ
ijassa-1239	126	10	distribution	distribution	NOUN
ijassa-1239	126	11	is	be	AUX
ijassa-1239	126	12	given	give	VERB
ijassa-1239	126	13	by	by	ADP
ijassa-1239	126	14	:	:	PUNCT
ijassa-1239	126	15	mk	mk	PROPN
ijassa-1239	126	16	=	=	SYM
ijassa-1239	126	17	lα	lα	PROPN
ijassa-1239	126	18	1−	1−	NUM
ijassa-1239	126	19	(	(	PUNCT
ijassa-1239	126	20	l	l	NOUN
ijassa-1239	126	21	/	/	SYM
ijassa-1239	126	22	h)α	h)α	ADJ
ijassa-1239	126	23	α(lk−α	α(lk−α	PROPN
ijassa-1239	126	24	−hk−α	−hk−α	NUM
ijassa-1239	126	25	)	)	PUNCT
ijassa-1239	126	26	α−	α−	ADP
ijassa-1239	126	27	k	k	PROPN
ijassa-1239	126	28	,	,	PUNCT
ijassa-1239	126	29	α	α	PROPN
ijassa-1239	126	30	̸=	̸=	PROPN
ijassa-1239	126	31	k.	k.	PROPN
ijassa-1239	126	32	accordingly	accordingly	ADV
ijassa-1239	126	33	,	,	PUNCT
ijassa-1239	126	34	we	we	PRON
ijassa-1239	126	35	have	have	VERB
ijassa-1239	126	36	that	that	SCONJ
ijassa-1239	126	37	the	the	DET
ijassa-1239	126	38	average	average	ADJ
ijassa-1239	126	39	service	service	NOUN
ijassa-1239	126	40	time	time	NOUN
ijassa-1239	126	41	is	be	AUX
ijassa-1239	126	42	approximately	approximately	ADV
ijassa-1239	126	43	equal	equal	ADJ
ijassa-1239	126	44	to	to	ADP
ijassa-1239	126	45	4.22	4.22	NUM
ijassa-1239	126	46	ms	ms	NOUN
ijassa-1239	126	47	,	,	PUNCT
ijassa-1239	126	48	the	the	DET
ijassa-1239	126	49	variance	variance	NOUN
ijassa-1239	126	50	is	be	AUX
ijassa-1239	126	51	22.34	22.34	NUM
ijassa-1239	126	52	,	,	PUNCT
ijassa-1239	126	53	and	and	CCONJ
ijassa-1239	126	54	the	the	DET
ijassa-1239	126	55	coefficient	coefficient	NOUN
ijassa-1239	126	56	of	of	ADP
ijassa-1239	126	57	variation	variation	NOUN
ijassa-1239	126	58	,	,	PUNCT
ijassa-1239	126	59	which	which	PRON
ijassa-1239	126	60	is	be	AUX
ijassa-1239	126	61	the	the	DET
ijassa-1239	126	62	ratio	ratio	NOUN
ijassa-1239	126	63	of	of	ADP
ijassa-1239	126	64	the	the	DET
ijassa-1239	126	65	root	root	NOUN
ijassa-1239	126	66	of	of	ADP
ijassa-1239	126	67	the	the	DET
ijassa-1239	126	68	variance	variance	NOUN
ijassa-1239	126	69	to	to	ADP
ijassa-1239	126	70	the	the	DET
ijassa-1239	126	71	average	average	ADJ
ijassa-1239	126	72	value	value	NOUN
ijassa-1239	126	73	of	of	ADP
ijassa-1239	126	74	a	a	DET
ijassa-1239	126	75	random	random	ADJ
ijassa-1239	126	76	variable	variable	NOUN
ijassa-1239	126	77	,	,	PUNCT
ijassa-1239	126	78	will	will	AUX
ijassa-1239	126	79	be	be	AUX
ijassa-1239	126	80	approximately	approximately	ADV
ijassa-1239	126	81	cv	cv	PROPN
ijassa-1239	127	1	≈	≈	PROPN
ijassa-1239	127	2	1.22	1.22	NUM
ijassa-1239	127	3	.	.	PUNCT
ijassa-1239	128	1	to	to	PART
ijassa-1239	128	2	distribute	distribute	VERB
ijassa-1239	128	3	the	the	DET
ijassa-1239	128	4	incoming	incoming	ADJ
ijassa-1239	128	5	flow	flow	NOUN
ijassa-1239	128	6	,	,	PUNCT
ijassa-1239	128	7	consider	consider	VERB
ijassa-1239	128	8	several	several	ADJ
ijassa-1239	128	9	options	option	NOUN
ijassa-1239	128	10	.	.	PUNCT
ijassa-1239	129	1	since	since	SCONJ
ijassa-1239	129	2	some	some	DET
ijassa-1239	129	3	studies	study	NOUN
ijassa-1239	129	4	allow	allow	VERB
ijassa-1239	129	5	the	the	DET
ijassa-1239	129	6	assumption	assumption	NOUN
ijassa-1239	129	7	of	of	ADP
ijassa-1239	129	8	the	the	DET
ijassa-1239	129	9	poisson	poisson	NOUN
ijassa-1239	129	10	nature	nature	NOUN
ijassa-1239	129	11	of	of	ADP
ijassa-1239	129	12	the	the	DET
ijassa-1239	129	13	incoming	incoming	ADJ
ijassa-1239	129	14	flow	flow	NOUN
ijassa-1239	129	15	(	(	PUNCT
ijassa-1239	129	16	cv	cv	NOUN
ijassa-1239	129	17	=	=	SYM
ijassa-1239	129	18	1	1	NUM
ijassa-1239	129	19	)	)	PUNCT
ijassa-1239	129	20	for	for	ADP
ijassa-1239	129	21	data	data	NOUN
ijassa-1239	129	22	processing	processing	NOUN
ijassa-1239	129	23	centers	center	NOUN
ijassa-1239	129	24	[	[	X
ijassa-1239	129	25	13	13	NUM
ijassa-1239	129	26	,	,	PUNCT
ijassa-1239	129	27	16	16	NUM
ijassa-1239	129	28	]	]	PUNCT
ijassa-1239	129	29	,	,	PUNCT
ijassa-1239	129	30	we	we	PRON
ijassa-1239	129	31	will	will	AUX
ijassa-1239	129	32	not	not	PART
ijassa-1239	129	33	exclude	exclude	VERB
ijassa-1239	129	34	the	the	DET
ijassa-1239	129	35	case	case	NOUN
ijassa-1239	129	36	of	of	ADP
ijassa-1239	129	37	an	an	DET
ijassa-1239	129	38	exponential	exponential	ADJ
ijassa-1239	129	39	distribution	distribution	NOUN
ijassa-1239	129	40	for	for	ADP
ijassa-1239	129	41	the	the	DET
ijassa-1239	129	42	time	time	NOUN
ijassa-1239	129	43	interval	interval	NOUN
ijassa-1239	129	44	between	between	ADP
ijassa-1239	129	45	adjacent	adjacent	ADJ
ijassa-1239	129	46	incoming	incoming	ADJ
ijassa-1239	129	47	requests	request	NOUN
ijassa-1239	129	48	.	.	PUNCT
ijassa-1239	130	1	we	we	PRON
ijassa-1239	130	2	also	also	ADV
ijassa-1239	130	3	consider	consider	VERB
ijassa-1239	130	4	two	two	NUM
ijassa-1239	130	5	more	more	ADJ
ijassa-1239	130	6	types	type	NOUN
ijassa-1239	130	7	of	of	ADP
ijassa-1239	130	8	distribution	distribution	NOUN
ijassa-1239	130	9	for	for	ADP
ijassa-1239	130	10	the	the	DET
ijassa-1239	130	11	incoming	incoming	ADJ
ijassa-1239	130	12	flow	flow	NOUN
ijassa-1239	130	13	with	with	ADP
ijassa-1239	130	14	a	a	DET
ijassa-1239	130	15	coefficient	coefficient	NOUN
ijassa-1239	130	16	of	of	ADP
ijassa-1239	130	17	variation	variation	NOUN
ijassa-1239	130	18	different	different	ADJ
ijassa-1239	130	19	from	from	ADP
ijassa-1239	130	20	unity	unity	NOUN
ijassa-1239	130	21	.	.	PUNCT
ijassa-1239	131	1	in	in	ADP
ijassa-1239	131	2	particular	particular	ADJ
ijassa-1239	131	3	,	,	PUNCT
ijassa-1239	131	4	for	for	ADP
ijassa-1239	131	5	the	the	DET
ijassa-1239	131	6	erlang	erlang	PROPN
ijassa-1239	131	7	distribution	distribution	NOUN
ijassa-1239	131	8	it	it	PRON
ijassa-1239	131	9	is	be	AUX
ijassa-1239	131	10	known	know	VERB
ijassa-1239	131	11	that	that	SCONJ
ijassa-1239	131	12	its	its	PRON
ijassa-1239	131	13	coefficient	coefficient	NOUN
ijassa-1239	131	14	of	of	ADP
ijassa-1239	131	15	variation	variation	NOUN
ijassa-1239	131	16	is	be	AUX
ijassa-1239	131	17	always	always	ADV
ijassa-1239	131	18	less	less	ADJ
ijassa-1239	131	19	than	than	ADP
ijassa-1239	131	20	one	one	NUM
ijassa-1239	131	21	.	.	PUNCT
ijassa-1239	132	1	therefore	therefore	ADV
ijassa-1239	132	2	,	,	PUNCT
ijassa-1239	132	3	consider	consider	VERB
ijassa-1239	132	4	the	the	DET
ijassa-1239	132	5	erlang	erlang	NOUN
ijassa-1239	132	6	distribution	distribution	NOUN
ijassa-1239	132	7	with	with	ADP
ijassa-1239	132	8	a	a	DET
ijassa-1239	132	9	density	density	NOUN
ijassa-1239	132	10	of	of	ADP
ijassa-1239	132	11	the	the	DET
ijassa-1239	132	12	form	form	NOUN
ijassa-1239	132	13	f1(x	f1(x	NOUN
ijassa-1239	132	14	)	)	PUNCT
ijassa-1239	132	15	=	=	SYM
ijassa-1239	132	16	β2xe−βx	β2xe−βx	PROPN
ijassa-1239	132	17	,	,	PUNCT
ijassa-1239	132	18	x	x	NOUN
ijassa-1239	132	19	⩾	⩾	NOUN
ijassa-1239	132	20	0	0	NUM
ijassa-1239	132	21	,	,	PUNCT
ijassa-1239	132	22	β	β	X
ijassa-1239	132	23	>	>	X
ijassa-1239	132	24	0	0	NUM
ijassa-1239	132	25	,	,	PUNCT
ijassa-1239	132	26	(	(	PUNCT
ijassa-1239	132	27	4.2	4.2	NUM
ijassa-1239	132	28	)	)	PUNCT
ijassa-1239	132	29	and	and	CCONJ
ijassa-1239	132	30	with	with	ADP
ijassa-1239	132	31	cv	cv	PROPN
ijassa-1239	132	32	=	=	SYM
ijassa-1239	132	33	1/	1/	NUM
ijassa-1239	132	34	√	√	NUM
ijassa-1239	132	35	2	2	NUM
ijassa-1239	132	36	≈	≈	PROPN
ijassa-1239	132	37	0.7	0.7	NUM
ijassa-1239	132	38	.	.	PUNCT
ijassa-1239	133	1	we	we	PRON
ijassa-1239	133	2	also	also	ADV
ijassa-1239	133	3	consider	consider	VERB
ijassa-1239	133	4	a	a	DET
ijassa-1239	133	5	heavy	heavy	ADJ
ijassa-1239	133	6	-	-	PUNCT
ijassa-1239	133	7	tailed	tail	VERB
ijassa-1239	133	8	distribution	distribution	NOUN
ijassa-1239	133	9	(	(	PUNCT
ijassa-1239	133	10	cv	cv	PROPN
ijassa-1239	133	11	>	>	X
ijassa-1239	133	12	1	1	NUM
ijassa-1239	133	13	)	)	PUNCT
ijassa-1239	133	14	,	,	PUNCT
ijassa-1239	133	15	namely	namely	ADV
ijassa-1239	133	16	the	the	DET
ijassa-1239	133	17	gamma	gamma	NOUN
ijassa-1239	133	18	distribution	distribution	NOUN
ijassa-1239	133	19	with	with	ADP
ijassa-1239	133	20	density	density	NOUN
ijassa-1239	133	21	f2(x	f2(x	NOUN
ijassa-1239	133	22	)	)	PUNCT
ijassa-1239	133	23	=	=	SYM
ijassa-1239	133	24	γk	γk	PROPN
ijassa-1239	133	25	γ(k	γ(k	PROPN
ijassa-1239	133	26	)	)	PUNCT
ijassa-1239	133	27	xk−1e−γx	xk−1e−γx	PROPN
ijassa-1239	133	28	,	,	PUNCT
ijassa-1239	133	29	x	x	X
ijassa-1239	133	30	⩾	⩾	NOUN
ijassa-1239	133	31	0	0	NUM
ijassa-1239	133	32	,	,	PUNCT
ijassa-1239	133	33	γ	γ	X
ijassa-1239	133	34	>	>	X
ijassa-1239	133	35	0	0	PROPN
ijassa-1239	133	36	,	,	PUNCT
ijassa-1239	133	37	k	k	PROPN
ijassa-1239	133	38	>	>	X
ijassa-1239	133	39	0	0	PUNCT
ijassa-1239	133	40	(	(	PUNCT
ijassa-1239	133	41	4.3	4.3	NUM
ijassa-1239	133	42	)	)	PUNCT
ijassa-1239	134	1	for	for	ADP
ijassa-1239	134	2	which	which	PRON
ijassa-1239	134	3	the	the	DET
ijassa-1239	134	4	coefficient	coefficient	NOUN
ijassa-1239	134	5	of	of	ADP
ijassa-1239	134	6	variation	variation	NOUN
ijassa-1239	134	7	cv	cv	PROPN
ijassa-1239	134	8	=	=	SYM
ijassa-1239	134	9	1/	1/	PROPN
ijassa-1239	134	10	√	√	PROPN
ijassa-1239	134	11	k	k	PROPN
ijassa-1239	134	12	for	for	ADP
ijassa-1239	134	13	k	k	X
ijassa-1239	134	14	=	=	NOUN
ijassa-1239	134	15	0.25	0.25	NUM
ijassa-1239	134	16	will	will	AUX
ijassa-1239	134	17	be	be	AUX
ijassa-1239	134	18	equal	equal	ADJ
ijassa-1239	134	19	to	to	ADP
ijassa-1239	134	20	2	2	NUM
ijassa-1239	134	21	.	.	NOUN
ijassa-1239	134	22	5	5	NUM
ijassa-1239	134	23	.	.	NOUN
ijassa-1239	134	24	numerical	numerical	PROPN
ijassa-1239	134	25	experiment	experiment	NOUN
ijassa-1239	134	26	let	let	VERB
ijassa-1239	134	27	’s	’s	PRON
ijassa-1239	134	28	check	check	VERB
ijassa-1239	134	29	the	the	DET
ijassa-1239	134	30	performance	performance	NOUN
ijassa-1239	134	31	and	and	CCONJ
ijassa-1239	134	32	quality	quality	NOUN
ijassa-1239	134	33	of	of	ADP
ijassa-1239	134	34	the	the	DET
ijassa-1239	134	35	approximation	approximation	NOUN
ijassa-1239	134	36	of	of	ADP
ijassa-1239	134	37	the	the	DET
ijassa-1239	134	38	proposed	propose	VERB
ijassa-1239	134	39	approach	approach	NOUN
ijassa-1239	134	40	using	use	VERB
ijassa-1239	134	41	neural	neural	ADJ
ijassa-1239	134	42	networks	network	NOUN
ijassa-1239	134	43	.	.	PUNCT
ijassa-1239	135	1	the	the	DET
ijassa-1239	135	2	first	first	ADJ
ijassa-1239	135	3	version	version	NOUN
ijassa-1239	135	4	of	of	ADP
ijassa-1239	135	5	the	the	DET
ijassa-1239	135	6	data	datum	NOUN
ijassa-1239	135	7	center	center	NOUN
ijassa-1239	135	8	architecture	architecture	NOUN
ijassa-1239	135	9	is	be	AUX
ijassa-1239	135	10	a	a	DET
ijassa-1239	135	11	fork	fork	NOUN
ijassa-1239	135	12	-	-	PUNCT
ijassa-1239	135	13	join	join	NOUN
ijassa-1239	135	14	qs	qs	NOUN
ijassa-1239	135	15	with	with	ADP
ijassa-1239	135	16	a	a	DET
ijassa-1239	135	17	poisson	poisson	NOUN
ijassa-1239	135	18	input	input	NOUN
ijassa-1239	135	19	flow	flow	NOUN
ijassa-1239	135	20	with	with	ADP
ijassa-1239	135	21	an	an	DET
ijassa-1239	135	22	intensity	intensity	NOUN
ijassa-1239	135	23	λ	λ	X
ijassa-1239	135	24	inversely	inversely	ADV
ijassa-1239	135	25	proportional	proportional	ADJ
ijassa-1239	135	26	to	to	ADP
ijassa-1239	135	27	the	the	DET
ijassa-1239	135	28	average	average	ADJ
ijassa-1239	135	29	time	time	NOUN
ijassa-1239	135	30	between	between	ADP
ijassa-1239	135	31	adjacent	adjacent	ADJ
ijassa-1239	135	32	arrivals	arrival	NOUN
ijassa-1239	135	33	of	of	ADP
ijassa-1239	135	34	requests	request	NOUN
ijassa-1239	135	35	a	a	DET
ijassa-1239	135	36	=	=	SYM
ijassa-1239	135	37	1	1	NUM
ijassa-1239	135	38	/	/	SYM
ijassa-1239	135	39	λ	λ	NOUN
ijassa-1239	135	40	.	.	PUNCT
ijassa-1239	136	1	the	the	DET
ijassa-1239	136	2	service	service	NOUN
ijassa-1239	136	3	time	time	NOUN
ijassa-1239	136	4	has	have	VERB
ijassa-1239	136	5	a	a	DET
ijassa-1239	136	6	truncated	truncate	VERB
ijassa-1239	136	7	pareto	pareto	ADJ
ijassa-1239	136	8	distribution	distribution	NOUN
ijassa-1239	136	9	with	with	ADP
ijassa-1239	136	10	parameters	parameter	NOUN
ijassa-1239	136	11	from	from	ADP
ijassa-1239	136	12	(	(	PUNCT
ijassa-1239	136	13	4.1	4.1	NUM
ijassa-1239	136	14	)	)	PUNCT
ijassa-1239	136	15	with	with	ADP
ijassa-1239	136	16	an	an	DET
ijassa-1239	136	17	average	average	ADJ
ijassa-1239	136	18	value	value	NOUN
ijassa-1239	136	19	of	of	ADP
ijassa-1239	136	20	b	b	NOUN
ijassa-1239	136	21	=	=	SYM
ijassa-1239	136	22	4.22	4.22	NUM
ijassa-1239	136	23	ms	ms	PROPN
ijassa-1239	136	24	.	.	PROPN
ijassa-1239	137	1	in	in	ADP
ijassa-1239	137	2	fact	fact	NOUN
ijassa-1239	137	3	,	,	PUNCT
ijassa-1239	137	4	each	each	DET
ijassa-1239	137	5	subsystem	subsystem	NOUN
ijassa-1239	137	6	is	be	AUX
ijassa-1239	137	7	a	a	DET
ijassa-1239	137	8	qs	qs	NOUN
ijassa-1239	137	9	of	of	ADP
ijassa-1239	137	10	the	the	DET
ijassa-1239	137	11	form	form	NOUN
ijassa-1239	137	12	m	m	VERB
ijassa-1239	137	13	|g|n	|g|n	PROPN
ijassa-1239	137	14	.	.	PUNCT
ijassa-1239	138	1	copyright	copyright	NOUN
ijassa-1239	138	2	©	©	PROPN
ijassa-1239	138	3	2022	2022	NUM
ijassa-1239	138	4	assa	assa	NOUN
ijassa-1239	138	5	.	.	PUNCT
ijassa-1239	139	1	adv	adv	PROPN
ijassa-1239	139	2	syst	syst	PROPN
ijassa-1239	139	3	sci	sci	PROPN
ijassa-1239	139	4	appl	appl	PROPN
ijassa-1239	139	5	(	(	PUNCT
ijassa-1239	139	6	2022	2022	NUM
ijassa-1239	139	7	)	)	PUNCT
ijassa-1239	139	8	76	76	NUM
ijassa-1239	139	9	a.v	a.v	PROPN
ijassa-1239	139	10	.	.	PROPN
ijassa-1239	139	11	gorbunova	gorbunova	PROPN
ijassa-1239	139	12	,	,	PUNCT
ijassa-1239	139	13	v.m	v.m	PROPN
ijassa-1239	139	14	.	.	PROPN
ijassa-1239	139	15	vishnevsky	vishnevsky	PROPN
ijassa-1239	139	16	to	to	PART
ijassa-1239	139	17	train	train	VERB
ijassa-1239	139	18	the	the	DET
ijassa-1239	139	19	neural	neural	ADJ
ijassa-1239	139	20	network	network	NOUN
ijassa-1239	139	21	,	,	PUNCT
ijassa-1239	139	22	we	we	PRON
ijassa-1239	139	23	will	will	AUX
ijassa-1239	139	24	use	use	VERB
ijassa-1239	139	25	the	the	DET
ijassa-1239	139	26	input	input	NOUN
ijassa-1239	139	27	data	datum	NOUN
ijassa-1239	139	28	from	from	ADP
ijassa-1239	139	29	the	the	DET
ijassa-1239	139	30	table	table	NOUN
ijassa-1239	139	31	5.1	5.1	NUM
ijassa-1239	139	32	,	,	PUNCT
ijassa-1239	139	33	where	where	SCONJ
ijassa-1239	139	34	the	the	DET
ijassa-1239	139	35	load	load	NOUN
ijassa-1239	139	36	factor	factor	NOUN
ijassa-1239	139	37	ρ	ρ	NOUN
ijassa-1239	139	38	=	=	SYM
ijassa-1239	139	39	b	b	PROPN
ijassa-1239	139	40	na	na	NOUN
ijassa-1239	139	41	=	=	SYM
ijassa-1239	139	42	λb	λb	NOUN
ijassa-1239	139	43	n	n	NOUN
ijassa-1239	139	44	takes	take	VERB
ijassa-1239	139	45	values	value	NOUN
ijassa-1239	139	46	on	on	ADP
ijassa-1239	139	47	the	the	DET
ijassa-1239	139	48	segment	segment	NOUN
ijassa-1239	139	49	[	[	X
ijassa-1239	139	50	0.1	0.1	NUM
ijassa-1239	139	51	,	,	PUNCT
ijassa-1239	139	52	0.9	0.9	NUM
ijassa-1239	139	53	]	]	PUNCT
ijassa-1239	139	54	with	with	ADP
ijassa-1239	139	55	a	a	DET
ijassa-1239	139	56	step	step	NOUN
ijassa-1239	139	57	of	of	ADP
ijassa-1239	139	58	0.1	0.1	NUM
ijassa-1239	139	59	,	,	PUNCT
ijassa-1239	139	60	the	the	DET
ijassa-1239	139	61	number	number	NOUN
ijassa-1239	139	62	of	of	ADP
ijassa-1239	139	63	subsystems	subsystem	NOUN
ijassa-1239	139	64	k	k	PROPN
ijassa-1239	139	65	varies	vary	VERB
ijassa-1239	139	66	from	from	ADP
ijassa-1239	139	67	2	2	NUM
ijassa-1239	139	68	to	to	ADP
ijassa-1239	139	69	24	24	NUM
ijassa-1239	139	70	,	,	PUNCT
ijassa-1239	139	71	and	and	CCONJ
ijassa-1239	139	72	the	the	DET
ijassa-1239	139	73	number	number	NOUN
ijassa-1239	139	74	of	of	ADP
ijassa-1239	139	75	servers	server	NOUN
ijassa-1239	139	76	n	n	CCONJ
ijassa-1239	139	77	from	from	ADP
ijassa-1239	139	78	1	1	NUM
ijassa-1239	139	79	to	to	ADP
ijassa-1239	139	80	3	3	NUM
ijassa-1239	139	81	.	.	PUNCT
ijassa-1239	140	1	the	the	DET
ijassa-1239	140	2	output	output	NOUN
ijassa-1239	140	3	of	of	ADP
ijassa-1239	140	4	the	the	DET
ijassa-1239	140	5	neural	neural	ADJ
ijassa-1239	140	6	network	network	NOUN
ijassa-1239	140	7	will	will	AUX
ijassa-1239	140	8	be	be	AUX
ijassa-1239	140	9	the	the	DET
ijassa-1239	140	10	mean	mean	ADJ
ijassa-1239	140	11	response	response	NOUN
ijassa-1239	140	12	time	time	NOUN
ijassa-1239	140	13	and	and	CCONJ
ijassa-1239	140	14	its	its	PRON
ijassa-1239	140	15	99th	99th	ADJ
ijassa-1239	140	16	percentile	percentile	NOUN
ijassa-1239	140	17	.	.	PUNCT
ijassa-1239	141	1	the	the	DET
ijassa-1239	141	2	values	value	NOUN
ijassa-1239	141	3	of	of	ADP
ijassa-1239	141	4	the	the	DET
ijassa-1239	141	5	output	output	NOUN
ijassa-1239	141	6	parameters	parameter	NOUN
ijassa-1239	141	7	were	be	AUX
ijassa-1239	141	8	obtained	obtain	VERB
ijassa-1239	141	9	by	by	ADP
ijassa-1239	141	10	using	use	VERB
ijassa-1239	141	11	simulations	simulation	NOUN
ijassa-1239	141	12	carried	carry	VERB
ijassa-1239	141	13	out	out	ADP
ijassa-1239	141	14	in	in	ADP
ijassa-1239	141	15	the	the	DET
ijassa-1239	141	16	python	python	NOUN
ijassa-1239	141	17	software	software	NOUN
ijassa-1239	141	18	environment	environment	NOUN
ijassa-1239	141	19	.	.	PUNCT
ijassa-1239	142	1	table	table	NOUN
ijassa-1239	142	2	5.1	5.1	NUM
ijassa-1239	142	3	.	.	PUNCT
ijassa-1239	143	1	input	input	NOUN
ijassa-1239	143	2	data	datum	NOUN
ijassa-1239	143	3	for	for	ADP
ijassa-1239	143	4	constructing	construct	VERB
ijassa-1239	143	5	estimates	estimate	NOUN
ijassa-1239	143	6	of	of	ADP
ijassa-1239	143	7	the	the	DET
ijassa-1239	143	8	mean	mean	ADJ
ijassa-1239	143	9	response	response	NOUN
ijassa-1239	143	10	time	time	NOUN
ijassa-1239	143	11	and	and	CCONJ
ijassa-1239	143	12	its	its	PRON
ijassa-1239	143	13	tail	tail	NOUN
ijassa-1239	143	14	delay	delay	NOUN
ijassa-1239	143	15	.	.	PUNCT
ijassa-1239	144	1	no	no	INTJ
ijassa-1239	144	2	.	.	NOUN
ijassa-1239	144	3	1	1	NUM
ijassa-1239	144	4	2	2	NUM
ijassa-1239	144	5	...	...	PUNCT
ijassa-1239	144	6	9	9	NUM
ijassa-1239	144	7	10	10	NUM
ijassa-1239	144	8	...	...	PUNCT
ijassa-1239	144	9	27	27	NUM
ijassa-1239	144	10	28	28	NUM
ijassa-1239	144	11	29	29	NUM
ijassa-1239	144	12	...	...	PUNCT
ijassa-1239	144	13	621	621	NUM
ijassa-1239	144	14	ρ	ρ	NOUN
ijassa-1239	144	15	0.1	0.1	NUM
ijassa-1239	144	16	0.2	0.2	NUM
ijassa-1239	144	17	...	...	PUNCT
ijassa-1239	144	18	0.9	0.9	NUM
ijassa-1239	144	19	0.1	0.1	NUM
ijassa-1239	144	20	...	...	PUNCT
ijassa-1239	145	1	0.9	0.9	NUM
ijassa-1239	145	2	0.1	0.1	NUM
ijassa-1239	145	3	0.2	0.2	NUM
ijassa-1239	145	4	...	...	PUNCT
ijassa-1239	146	1	0.9	0.9	NUM
ijassa-1239	146	2	n	n	NOUN
ijassa-1239	146	3	1	1	NUM
ijassa-1239	146	4	1	1	NUM
ijassa-1239	146	5	...	...	SYM
ijassa-1239	146	6	1	1	NUM
ijassa-1239	146	7	2	2	NUM
ijassa-1239	146	8	...	...	SYM
ijassa-1239	146	9	3	3	NUM
ijassa-1239	146	10	1	1	NUM
ijassa-1239	146	11	1	1	NUM
ijassa-1239	146	12	...	...	SYM
ijassa-1239	146	13	3	3	NUM
ijassa-1239	146	14	k	k	NOUN
ijassa-1239	146	15	2	2	NUM
ijassa-1239	146	16	2	2	NUM
ijassa-1239	146	17	...	...	SYM
ijassa-1239	146	18	2	2	NUM
ijassa-1239	146	19	2	2	NUM
ijassa-1239	146	20	...	...	SYM
ijassa-1239	146	21	2	2	NUM
ijassa-1239	146	22	3	3	NUM
ijassa-1239	146	23	3	3	NUM
ijassa-1239	146	24	...	...	SYM
ijassa-1239	146	25	24	24	NUM
ijassa-1239	146	26	let	let	VERB
ijassa-1239	146	27	’s	’s	NOUN
ijassa-1239	146	28	split	split	VERB
ijassa-1239	146	29	the	the	DET
ijassa-1239	146	30	data	datum	NOUN
ijassa-1239	146	31	from	from	ADP
ijassa-1239	146	32	the	the	DET
ijassa-1239	146	33	table	table	NOUN
ijassa-1239	146	34	5.1	5.1	NUM
ijassa-1239	146	35	into	into	ADP
ijassa-1239	146	36	two	two	NUM
ijassa-1239	146	37	sets	set	NOUN
ijassa-1239	146	38	corresponding	correspond	VERB
ijassa-1239	146	39	to	to	ADP
ijassa-1239	146	40	the	the	DET
ijassa-1239	146	41	level	level	NOUN
ijassa-1239	146	42	of	of	ADP
ijassa-1239	146	43	low	low	ADJ
ijassa-1239	146	44	and	and	CCONJ
ijassa-1239	146	45	high	high	ADJ
ijassa-1239	146	46	loads	load	NOUN
ijassa-1239	146	47	,	,	PUNCT
ijassa-1239	146	48	i.e.	i.e.	X
ijassa-1239	146	49	for	for	ADP
ijassa-1239	146	50	ρ	ρ	PROPN
ijassa-1239	146	51	∈	∈	PROPN
ijassa-1239	147	1	[	[	X
ijassa-1239	147	2	0.1	0.1	NUM
ijassa-1239	147	3	,	,	PUNCT
ijassa-1239	147	4	0.5	0.5	NUM
ijassa-1239	147	5	]	]	PUNCT
ijassa-1239	147	6	and	and	CCONJ
ijassa-1239	147	7	ρ	ρ	NUM
ijassa-1239	147	8	∈	∈	PROPN
ijassa-1239	148	1	[	[	X
ijassa-1239	148	2	0.6	0.6	NUM
ijassa-1239	148	3	,	,	PUNCT
ijassa-1239	148	4	0.9	0.9	NUM
ijassa-1239	148	5	]	]	PUNCT
ijassa-1239	148	6	.	.	PUNCT
ijassa-1239	149	1	and	and	CCONJ
ijassa-1239	149	2	we	we	PRON
ijassa-1239	149	3	will	will	AUX
ijassa-1239	149	4	train	train	VERB
ijassa-1239	149	5	the	the	DET
ijassa-1239	149	6	neural	neural	ADJ
ijassa-1239	149	7	network	network	NOUN
ijassa-1239	149	8	on	on	ADP
ijassa-1239	149	9	each	each	PRON
ijassa-1239	149	10	of	of	ADP
ijassa-1239	149	11	these	these	DET
ijassa-1239	149	12	two	two	NUM
ijassa-1239	149	13	sets	set	NOUN
ijassa-1239	149	14	.	.	PUNCT
ijassa-1239	150	1	in	in	ADP
ijassa-1239	150	2	this	this	DET
ijassa-1239	150	3	case	case	NOUN
ijassa-1239	150	4	,	,	PUNCT
ijassa-1239	150	5	the	the	DET
ijassa-1239	150	6	data	datum	NOUN
ijassa-1239	150	7	set	set	VERB
ijassa-1239	150	8	is	be	AUX
ijassa-1239	150	9	divided	divide	VERB
ijassa-1239	150	10	in	in	ADP
ijassa-1239	150	11	the	the	DET
ijassa-1239	150	12	ratio	ratio	NOUN
ijassa-1239	150	13	of	of	ADP
ijassa-1239	150	14	80	80	NUM
ijassa-1239	150	15	%	%	NOUN
ijassa-1239	150	16	and	and	CCONJ
ijassa-1239	150	17	20	20	NUM
ijassa-1239	150	18	%	%	NOUN
ijassa-1239	150	19	into	into	ADP
ijassa-1239	150	20	training	training	NOUN
ijassa-1239	150	21	and	and	CCONJ
ijassa-1239	150	22	test	test	NOUN
ijassa-1239	150	23	samples	sample	NOUN
ijassa-1239	150	24	.	.	PUNCT
ijassa-1239	151	1	the	the	DET
ijassa-1239	151	2	latter	latter	ADJ
ijassa-1239	151	3	will	will	AUX
ijassa-1239	151	4	be	be	AUX
ijassa-1239	151	5	used	use	VERB
ijassa-1239	151	6	for	for	ADP
ijassa-1239	151	7	validation	validation	NOUN
ijassa-1239	151	8	during	during	ADP
ijassa-1239	151	9	training	training	NOUN
ijassa-1239	151	10	.	.	PUNCT
ijassa-1239	152	1	by	by	ADP
ijassa-1239	152	2	the	the	DET
ijassa-1239	152	3	standards	standard	NOUN
ijassa-1239	152	4	of	of	ADP
ijassa-1239	152	5	neural	neural	ADJ
ijassa-1239	152	6	networks	network	NOUN
ijassa-1239	152	7	,	,	PUNCT
ijassa-1239	152	8	it	it	PRON
ijassa-1239	152	9	can	can	AUX
ijassa-1239	152	10	not	not	PART
ijassa-1239	152	11	be	be	AUX
ijassa-1239	152	12	said	say	VERB
ijassa-1239	152	13	that	that	SCONJ
ijassa-1239	152	14	the	the	DET
ijassa-1239	152	15	number	number	NOUN
ijassa-1239	152	16	of	of	ADP
ijassa-1239	152	17	data	datum	NOUN
ijassa-1239	152	18	sets	set	NOUN
ijassa-1239	152	19	for	for	ADP
ijassa-1239	152	20	irradiation	irradiation	NOUN
ijassa-1239	152	21	is	be	AUX
ijassa-1239	152	22	large	large	ADJ
ijassa-1239	152	23	.	.	PUNCT
ijassa-1239	153	1	nevertheless	nevertheless	ADV
ijassa-1239	153	2	,	,	PUNCT
ijassa-1239	153	3	we	we	PRON
ijassa-1239	153	4	will	will	AUX
ijassa-1239	153	5	check	check	VERB
ijassa-1239	153	6	the	the	DET
ijassa-1239	153	7	accuracy	accuracy	NOUN
ijassa-1239	153	8	of	of	ADP
ijassa-1239	153	9	the	the	DET
ijassa-1239	153	10	proposed	propose	VERB
ijassa-1239	153	11	approach	approach	NOUN
ijassa-1239	153	12	under	under	ADP
ijassa-1239	153	13	these	these	DET
ijassa-1239	153	14	conditions	condition	NOUN
ijassa-1239	153	15	.	.	PUNCT
ijassa-1239	154	1	a	a	DET
ijassa-1239	154	2	two	two	NUM
ijassa-1239	154	3	-	-	PUNCT
ijassa-1239	154	4	layer	layer	NOUN
ijassa-1239	154	5	perceptron	perceptron	NOUN
ijassa-1239	154	6	with	with	ADP
ijassa-1239	154	7	two	two	NUM
ijassa-1239	154	8	hidden	hidden	ADJ
ijassa-1239	154	9	layers	layer	NOUN
ijassa-1239	154	10	of	of	ADP
ijassa-1239	154	11	10	10	NUM
ijassa-1239	154	12	neurons	neuron	NOUN
ijassa-1239	154	13	each	each	PRON
ijassa-1239	154	14	with	with	ADP
ijassa-1239	154	15	a	a	DET
ijassa-1239	154	16	logistic	logistic	ADJ
ijassa-1239	154	17	activation	activation	NOUN
ijassa-1239	154	18	function	function	NOUN
ijassa-1239	154	19	ϕ(x	ϕ(x	X
ijassa-1239	154	20	)	)	PUNCT
ijassa-1239	154	21	=	=	SYM
ijassa-1239	155	1	1/(1	1/(1	NUM
ijassa-1239	155	2	+	+	NUM
ijassa-1239	155	3	e−x	e−x	NOUN
ijassa-1239	155	4	)	)	PUNCT
ijassa-1239	155	5	was	be	AUX
ijassa-1239	155	6	chosen	choose	VERB
ijassa-1239	155	7	as	as	ADP
ijassa-1239	155	8	the	the	DET
ijassa-1239	155	9	neural	neural	ADJ
ijassa-1239	155	10	network	network	NOUN
ijassa-1239	155	11	structure	structure	NOUN
ijassa-1239	155	12	.	.	PUNCT
ijassa-1239	156	1	to	to	PART
ijassa-1239	156	2	improve	improve	VERB
ijassa-1239	156	3	the	the	DET
ijassa-1239	156	4	approximation	approximation	NOUN
ijassa-1239	156	5	accuracy	accuracy	NOUN
ijassa-1239	156	6	,	,	PUNCT
ijassa-1239	156	7	we	we	PRON
ijassa-1239	156	8	will	will	AUX
ijassa-1239	156	9	build	build	VERB
ijassa-1239	156	10	two	two	NUM
ijassa-1239	156	11	neural	neural	ADJ
ijassa-1239	156	12	networks	network	NOUN
ijassa-1239	156	13	:	:	PUNCT
ijassa-1239	156	14	the	the	DET
ijassa-1239	156	15	first	first	ADJ
ijassa-1239	156	16	one	one	NOUN
ijassa-1239	156	17	is	be	AUX
ijassa-1239	156	18	for	for	ADP
ijassa-1239	156	19	predicting	predict	VERB
ijassa-1239	156	20	the	the	DET
ijassa-1239	156	21	mean	mean	ADJ
ijassa-1239	156	22	response	response	NOUN
ijassa-1239	156	23	time	time	NOUN
ijassa-1239	156	24	e[rk	e[rk	PROPN
ijassa-1239	156	25	]	]	X
ijassa-1239	156	26	,	,	PUNCT
ijassa-1239	156	27	the	the	DET
ijassa-1239	156	28	second	second	ADJ
ijassa-1239	156	29	one	one	NOUN
ijassa-1239	156	30	is	be	AUX
ijassa-1239	156	31	for	for	SCONJ
ijassa-1239	156	32	the	the	DET
ijassa-1239	156	33	tail	tail	NOUN
ijassa-1239	156	34	delay	delay	NOUN
ijassa-1239	156	35	rk(99	rk(99	PROPN
ijassa-1239	156	36	)	)	PUNCT
ijassa-1239	156	37	.	.	PUNCT
ijassa-1239	157	1	training	training	NOUN
ijassa-1239	157	2	will	will	AUX
ijassa-1239	157	3	be	be	AUX
ijassa-1239	157	4	carried	carry	VERB
ijassa-1239	157	5	out	out	ADP
ijassa-1239	157	6	by	by	ADP
ijassa-1239	157	7	the	the	DET
ijassa-1239	157	8	method	method	NOUN
ijassa-1239	157	9	of	of	ADP
ijassa-1239	157	10	back	back	ADJ
ijassa-1239	157	11	propagation	propagation	NOUN
ijassa-1239	157	12	of	of	ADP
ijassa-1239	157	13	errors	error	NOUN
ijassa-1239	157	14	or	or	CCONJ
ijassa-1239	157	15	the	the	DET
ijassa-1239	157	16	adam	adam	PROPN
ijassa-1239	157	17	method	method	NOUN
ijassa-1239	157	18	in	in	ADP
ijassa-1239	157	19	the	the	DET
ijassa-1239	157	20	python	python	NOUN
ijassa-1239	157	21	software	software	NOUN
ijassa-1239	157	22	environment	environment	NOUN
ijassa-1239	157	23	,	,	PUNCT
ijassa-1239	157	24	where	where	SCONJ
ijassa-1239	157	25	simulation	simulation	NOUN
ijassa-1239	157	26	modeling	modeling	NOUN
ijassa-1239	157	27	was	be	AUX
ijassa-1239	157	28	carried	carry	VERB
ijassa-1239	157	29	out	out	ADP
ijassa-1239	157	30	.	.	PUNCT
ijassa-1239	158	1	for	for	ADP
ijassa-1239	158	2	an	an	DET
ijassa-1239	158	3	objective	objective	ADJ
ijassa-1239	158	4	check	check	NOUN
ijassa-1239	158	5	of	of	ADP
ijassa-1239	158	6	the	the	DET
ijassa-1239	158	7	forecast	forecast	NOUN
ijassa-1239	158	8	quality	quality	NOUN
ijassa-1239	158	9	of	of	ADP
ijassa-1239	158	10	trained	train	VERB
ijassa-1239	158	11	neural	neural	ADJ
ijassa-1239	158	12	networks	network	NOUN
ijassa-1239	158	13	,	,	PUNCT
ijassa-1239	158	14	we	we	PRON
ijassa-1239	158	15	will	will	AUX
ijassa-1239	158	16	use	use	VERB
ijassa-1239	158	17	intermediate	intermediate	ADJ
ijassa-1239	158	18	data	datum	NOUN
ijassa-1239	158	19	absolutely	absolutely	ADV
ijassa-1239	158	20	unknown	unknown	ADJ
ijassa-1239	158	21	to	to	ADP
ijassa-1239	158	22	it	it	PRON
ijassa-1239	158	23	from	from	ADP
ijassa-1239	158	24	the	the	DET
ijassa-1239	158	25	5.2	5.2	NUM
ijassa-1239	158	26	table	table	NOUN
ijassa-1239	158	27	.	.	PUNCT
ijassa-1239	159	1	for	for	ADP
ijassa-1239	159	2	a	a	DET
ijassa-1239	159	3	neural	neural	ADJ
ijassa-1239	159	4	network	network	NOUN
ijassa-1239	159	5	trained	train	VERB
ijassa-1239	159	6	in	in	ADP
ijassa-1239	159	7	the	the	DET
ijassa-1239	159	8	area	area	NOUN
ijassa-1239	159	9	of	of	ADP
ijassa-1239	159	10	low	low	ADJ
ijassa-1239	159	11	loads	load	NOUN
ijassa-1239	159	12	,	,	PUNCT
ijassa-1239	159	13	consider	consider	VERB
ijassa-1239	159	14	the	the	DET
ijassa-1239	159	15	values	value	NOUN
ijassa-1239	159	16	for	for	ADP
ijassa-1239	159	17	the	the	DET
ijassa-1239	159	18	prediction	prediction	NOUN
ijassa-1239	159	19	ρ	ρ	X
ijassa-1239	159	20	∈	∈	PROPN
ijassa-1239	160	1	[	[	X
ijassa-1239	160	2	0.15	0.15	NUM
ijassa-1239	160	3	,	,	PUNCT
ijassa-1239	160	4	0.55	0.55	NUM
ijassa-1239	160	5	]	]	PUNCT
ijassa-1239	160	6	,	,	PUNCT
ijassa-1239	160	7	and	and	CCONJ
ijassa-1239	160	8	for	for	ADP
ijassa-1239	160	9	a	a	DET
ijassa-1239	160	10	neural	neural	ADJ
ijassa-1239	160	11	network	network	NOUN
ijassa-1239	160	12	trained	train	VERB
ijassa-1239	160	13	in	in	ADP
ijassa-1239	160	14	the	the	DET
ijassa-1239	160	15	area	area	NOUN
ijassa-1239	160	16	of	of	ADP
ijassa-1239	160	17	higher	high	ADJ
ijassa-1239	160	18	loads	load	NOUN
ijassa-1239	160	19	ρ	ρ	PROPN
ijassa-1239	160	20	∈	∈	PROPN
ijassa-1239	161	1	[	[	X
ijassa-1239	161	2	0.65	0.65	NUM
ijassa-1239	161	3	,	,	PUNCT
ijassa-1239	161	4	0.85	0.85	NUM
ijassa-1239	161	5	]	]	PUNCT
ijassa-1239	161	6	.	.	PUNCT
ijassa-1239	162	1	table	table	NOUN
ijassa-1239	162	2	5.2	5.2	NUM
ijassa-1239	162	3	.	.	PUNCT
ijassa-1239	163	1	intermediate	intermediate	ADJ
ijassa-1239	163	2	input	input	NOUN
ijassa-1239	163	3	data	datum	NOUN
ijassa-1239	163	4	for	for	ADP
ijassa-1239	163	5	constructing	construct	VERB
ijassa-1239	163	6	estimates	estimate	NOUN
ijassa-1239	163	7	of	of	ADP
ijassa-1239	163	8	the	the	DET
ijassa-1239	163	9	mean	mean	ADJ
ijassa-1239	163	10	response	response	NOUN
ijassa-1239	163	11	time	time	NOUN
ijassa-1239	163	12	and	and	CCONJ
ijassa-1239	163	13	its	its	PRON
ijassa-1239	163	14	tail	tail	NOUN
ijassa-1239	163	15	delay	delay	NOUN
ijassa-1239	163	16	.	.	PUNCT
ijassa-1239	164	1	no	no	INTJ
ijassa-1239	164	2	.	.	NOUN
ijassa-1239	164	3	1	1	NUM
ijassa-1239	164	4	2	2	NUM
ijassa-1239	164	5	...	...	SYM
ijassa-1239	164	6	8	8	NUM
ijassa-1239	164	7	9	9	NUM
ijassa-1239	164	8	...	...	SYM
ijassa-1239	164	9	24	24	NUM
ijassa-1239	164	10	25	25	NUM
ijassa-1239	164	11	26	26	NUM
ijassa-1239	164	12	...	...	PUNCT
ijassa-1239	164	13	552	552	NUM
ijassa-1239	164	14	ρ	ρ	NUM
ijassa-1239	164	15	0.15	0.15	NUM
ijassa-1239	164	16	0.25	0.25	NUM
ijassa-1239	164	17	...	...	PUNCT
ijassa-1239	165	1	0.85	0.85	NUM
ijassa-1239	165	2	0.15	0.15	NUM
ijassa-1239	165	3	...	...	PUNCT
ijassa-1239	166	1	0.85	0.85	NUM
ijassa-1239	166	2	0.15	0.15	NUM
ijassa-1239	166	3	0.25	0.25	NUM
ijassa-1239	166	4	...	...	PUNCT
ijassa-1239	167	1	0.85	0.85	NUM
ijassa-1239	167	2	n	n	CCONJ
ijassa-1239	167	3	1	1	NUM
ijassa-1239	167	4	1	1	NUM
ijassa-1239	167	5	...	...	SYM
ijassa-1239	167	6	1	1	NUM
ijassa-1239	167	7	2	2	NUM
ijassa-1239	167	8	...	...	SYM
ijassa-1239	167	9	3	3	NUM
ijassa-1239	167	10	1	1	NUM
ijassa-1239	167	11	1	1	NUM
ijassa-1239	167	12	...	...	SYM
ijassa-1239	167	13	3	3	NUM
ijassa-1239	167	14	k	k	NOUN
ijassa-1239	167	15	2	2	NUM
ijassa-1239	167	16	2	2	NUM
ijassa-1239	167	17	...	...	SYM
ijassa-1239	167	18	2	2	NUM
ijassa-1239	167	19	2	2	NUM
ijassa-1239	167	20	...	...	SYM
ijassa-1239	167	21	2	2	NUM
ijassa-1239	167	22	3	3	NUM
ijassa-1239	167	23	3	3	NUM
ijassa-1239	167	24	...	...	PUNCT
ijassa-1239	167	25	24	24	NUM
ijassa-1239	167	26	the	the	DET
ijassa-1239	167	27	figures	figure	NOUN
ijassa-1239	167	28	5.3	5.3	NUM
ijassa-1239	167	29	show	show	VERB
ijassa-1239	167	30	the	the	DET
ijassa-1239	167	31	deviation	deviation	NOUN
ijassa-1239	167	32	of	of	ADP
ijassa-1239	167	33	the	the	DET
ijassa-1239	167	34	estimates	estimate	NOUN
ijassa-1239	167	35	of	of	ADP
ijassa-1239	167	36	the	the	DET
ijassa-1239	167	37	studied	studied	ADJ
ijassa-1239	167	38	characteristics	characteristic	NOUN
ijassa-1239	167	39	from	from	ADP
ijassa-1239	167	40	their	their	PRON
ijassa-1239	167	41	true	true	ADJ
ijassa-1239	167	42	values	value	NOUN
ijassa-1239	167	43	obtained	obtain	VERB
ijassa-1239	167	44	using	use	VERB
ijassa-1239	167	45	simulation	simulation	NOUN
ijassa-1239	167	46	modeling	modeling	NOUN
ijassa-1239	167	47	.	.	PUNCT
ijassa-1239	168	1	for	for	ADP
ijassa-1239	168	2	more	more	ADJ
ijassa-1239	168	3	detail	detail	NOUN
ijassa-1239	168	4	,	,	PUNCT
ijassa-1239	168	5	let	let	VERB
ijassa-1239	168	6	’s	’s	PRON
ijassa-1239	168	7	analyze	analyze	VERB
ijassa-1239	168	8	the	the	DET
ijassa-1239	168	9	relative	relative	ADJ
ijassa-1239	168	10	approximation	approximation	NOUN
ijassa-1239	168	11	error	error	NOUN
ijassa-1239	168	12	pe	pe	NOUN
ijassa-1239	168	13	=	=	PUNCT
ijassa-1239	168	14	∣∣∣∣	∣∣∣∣	PROPN
ijassa-1239	168	15	x̂j	x̂j	PROPN
ijassa-1239	168	16	−	−	PROPN
ijassa-1239	168	17	xj	xj	PROPN
ijassa-1239	168	18	xj	xj	PROPN
ijassa-1239	168	19	∣∣∣∣	∣∣∣∣	PROPN
ijassa-1239	168	20	·	·	PUNCT
ijassa-1239	168	21	100	100	NUM
ijassa-1239	168	22	%	%	NOUN
ijassa-1239	168	23	for	for	ADP
ijassa-1239	168	24	each	each	DET
ijassa-1239	168	25	set	set	NOUN
ijassa-1239	168	26	of	of	ADP
ijassa-1239	168	27	intermediate	intermediate	ADJ
ijassa-1239	168	28	input	input	NOUN
ijassa-1239	168	29	data	datum	NOUN
ijassa-1239	168	30	,	,	PUNCT
ijassa-1239	168	31	as	as	ADV
ijassa-1239	168	32	well	well	ADV
ijassa-1239	168	33	as	as	ADP
ijassa-1239	168	34	its	its	PRON
ijassa-1239	168	35	average	average	ADJ
ijassa-1239	168	36	value	value	NOUN
ijassa-1239	168	37	mape	mape	NOUN
ijassa-1239	168	38	=	=	SYM
ijassa-1239	168	39	1	1	NUM
ijassa-1239	168	40	n	n	NUM
ijassa-1239	168	41	n∑	n∑	ADJ
ijassa-1239	168	42	j=1	j=1	PROPN
ijassa-1239	168	43	∣∣∣∣	∣∣∣∣	PROPN
ijassa-1239	168	44	x̂j	x̂j	PROPN
ijassa-1239	168	45	−	−	PROPN
ijassa-1239	168	46	xj	xj	PROPN
ijassa-1239	168	47	xj	xj	PROPN
ijassa-1239	168	48	∣∣∣∣	∣∣∣∣	PROPN
ijassa-1239	168	49	·	·	PUNCT
ijassa-1239	168	50	100	100	NUM
ijassa-1239	168	51	%	%	NOUN
ijassa-1239	168	52	,	,	PUNCT
ijassa-1239	168	53	where	where	SCONJ
ijassa-1239	168	54	x̂j	x̂j	PROPN
ijassa-1239	168	55	is	be	AUX
ijassa-1239	168	56	an	an	DET
ijassa-1239	168	57	estimate	estimate	NOUN
ijassa-1239	168	58	of	of	ADP
ijassa-1239	168	59	the	the	DET
ijassa-1239	168	60	characteristic	characteristic	NOUN
ijassa-1239	168	61	under	under	ADP
ijassa-1239	168	62	study	study	NOUN
ijassa-1239	168	63	(	(	PUNCT
ijassa-1239	168	64	mean	mean	INTJ
ijassa-1239	168	65	value	value	NOUN
ijassa-1239	168	66	or	or	CCONJ
ijassa-1239	168	67	tail	tail	NOUN
ijassa-1239	168	68	delay	delay	NOUN
ijassa-1239	168	69	of	of	ADP
ijassa-1239	168	70	the	the	DET
ijassa-1239	168	71	response	response	NOUN
ijassa-1239	168	72	time	time	NOUN
ijassa-1239	168	73	)	)	PUNCT
ijassa-1239	168	74	,	,	PUNCT
ijassa-1239	168	75	obtained	obtain	VERB
ijassa-1239	168	76	by	by	ADP
ijassa-1239	168	77	using	use	VERB
ijassa-1239	168	78	analytical	analytical	ADJ
ijassa-1239	168	79	formulas	formula	NOUN
ijassa-1239	168	80	,	,	PUNCT
ijassa-1239	168	81	and	and	CCONJ
ijassa-1239	168	82	xj	xj	PROPN
ijassa-1239	168	83	is	be	AUX
ijassa-1239	168	84	the	the	DET
ijassa-1239	168	85	real	real	ADJ
ijassa-1239	168	86	value	value	NOUN
ijassa-1239	168	87	of	of	ADP
ijassa-1239	168	88	one	one	NUM
ijassa-1239	168	89	of	of	ADP
ijassa-1239	168	90	the	the	DET
ijassa-1239	168	91	copyright	copyright	NOUN
ijassa-1239	168	92	©	©	ADP
ijassa-1239	168	93	2022	2022	NUM
ijassa-1239	168	94	assa	assa	NOUN
ijassa-1239	168	95	.	.	PUNCT
ijassa-1239	169	1	adv	adv	PROPN
ijassa-1239	169	2	syst	syst	PROPN
ijassa-1239	169	3	sci	sci	PROPN
ijassa-1239	169	4	appl	appl	PROPN
ijassa-1239	169	5	(	(	PUNCT
ijassa-1239	169	6	2022	2022	NUM
ijassa-1239	169	7	)	)	PUNCT
ijassa-1239	169	8	the	the	DET
ijassa-1239	169	9	analysis	analysis	NOUN
ijassa-1239	169	10	of	of	ADP
ijassa-1239	169	11	big	big	ADJ
ijassa-1239	169	12	data	datum	NOUN
ijassa-1239	169	13	centers	center	NOUN
ijassa-1239	169	14	performance	performance	VERB
ijassa-1239	169	15	77	77	NUM
ijassa-1239	169	16	estimated	estimate	VERB
ijassa-1239	169	17	characteristics	characteristic	NOUN
ijassa-1239	169	18	,	,	PUNCT
ijassa-1239	169	19	obtained	obtain	VERB
ijassa-1239	169	20	as	as	ADP
ijassa-1239	169	21	a	a	DET
ijassa-1239	169	22	result	result	NOUN
ijassa-1239	169	23	of	of	ADP
ijassa-1239	169	24	fork	fork	NOUN
ijassa-1239	169	25	-	-	PUNCT
ijassa-1239	169	26	join	join	NOUN
ijassa-1239	169	27	qs	qs	PROPN
ijassa-1239	169	28	simulation	simulation	NOUN
ijassa-1239	169	29	,	,	PUNCT
ijassa-1239	169	30	j	j	PROPN
ijassa-1239	169	31	=	=	SYM
ijassa-1239	169	32	1	1	NUM
ijassa-1239	169	33	,	,	PUNCT
ijassa-1239	169	34	n	n	PRON
ijassa-1239	169	35	,	,	PUNCT
ijassa-1239	169	36	n	n	X
ijassa-1239	169	37	is	be	AUX
ijassa-1239	169	38	the	the	DET
ijassa-1239	169	39	number	number	NOUN
ijassa-1239	169	40	of	of	ADP
ijassa-1239	169	41	data	datum	NOUN
ijassa-1239	169	42	sets	set	NOUN
ijassa-1239	169	43	in	in	ADP
ijassa-1239	169	44	the	the	DET
ijassa-1239	169	45	sample	sample	NOUN
ijassa-1239	169	46	for	for	ADP
ijassa-1239	169	47	the	the	DET
ijassa-1239	169	48	estimation	estimation	NOUN
ijassa-1239	169	49	of	of	ADP
ijassa-1239	169	50	the	the	DET
ijassa-1239	169	51	approximation	approximation	NOUN
ijassa-1239	169	52	error	error	NOUN
ijassa-1239	169	53	.	.	PUNCT
ijassa-1239	170	1	5	5	NUM
ijassa-1239	170	2	15	15	NUM
ijassa-1239	170	3	25	25	NUM
ijassa-1239	170	4	35	35	NUM
ijassa-1239	170	5	45	45	NUM
ijassa-1239	170	6	55	55	NUM
ijassa-1239	170	7	65	65	NUM
ijassa-1239	170	8	5	5	NUM
ijassa-1239	170	9	15	15	NUM
ijassa-1239	170	10	25	25	NUM
ijassa-1239	170	11	35	35	NUM
ijassa-1239	170	12	45	45	NUM
ijassa-1239	170	13	55	55	NUM
ijassa-1239	170	14	65	65	NUM
ijassa-1239	170	15	a	a	DET
ijassa-1239	170	16	n	n	NUM
ijassa-1239	170	17	n	n	DET
ijassa-1239	170	18	simulation	simulation	NOUN
ijassa-1239	170	19	a	a	NOUN
ijassa-1239	170	20	)	)	PUNCT
ijassa-1239	170	21	5	5	NUM
ijassa-1239	170	22	25	25	NUM
ijassa-1239	170	23	45	45	NUM
ijassa-1239	170	24	65	65	NUM
ijassa-1239	170	25	85	85	NUM
ijassa-1239	170	26	105	105	NUM
ijassa-1239	170	27	125	125	NUM
ijassa-1239	170	28	145	145	NUM
ijassa-1239	170	29	165	165	NUM
ijassa-1239	170	30	5	5	NUM
ijassa-1239	170	31	25	25	NUM
ijassa-1239	170	32	45	45	NUM
ijassa-1239	170	33	65	65	NUM
ijassa-1239	170	34	85	85	NUM
ijassa-1239	170	35	105	105	NUM
ijassa-1239	170	36	125	125	NUM
ijassa-1239	170	37	145	145	NUM
ijassa-1239	170	38	165	165	NUM
ijassa-1239	170	39	a	a	DET
ijassa-1239	170	40	n	n	NUM
ijassa-1239	170	41	n	n	PRON
ijassa-1239	170	42	simulation	simulation	NOUN
ijassa-1239	170	43	b	b	PROPN
ijassa-1239	170	44	)	)	PUNCT
ijassa-1239	170	45	fig	fig	NOUN
ijassa-1239	170	46	.	.	PUNCT
ijassa-1239	171	1	5.3	5.3	NUM
ijassa-1239	171	2	.	.	PUNCT
ijassa-1239	172	1	the	the	DET
ijassa-1239	172	2	mean	mean	ADJ
ijassa-1239	172	3	response	response	NOUN
ijassa-1239	172	4	time	time	NOUN
ijassa-1239	172	5	of	of	ADP
ijassa-1239	172	6	a	a	DET
ijassa-1239	172	7	system	system	NOUN
ijassa-1239	172	8	with	with	ADP
ijassa-1239	172	9	poisson	poisson	PROPN
ijassa-1239	172	10	input	input	NOUN
ijassa-1239	172	11	,	,	PUNCT
ijassa-1239	172	12	a	a	DET
ijassa-1239	172	13	truncated	truncate	VERB
ijassa-1239	172	14	pareto	pareto	ADJ
ijassa-1239	172	15	distribution	distribution	NOUN
ijassa-1239	172	16	of	of	ADP
ijassa-1239	172	17	service	service	NOUN
ijassa-1239	172	18	time	time	NOUN
ijassa-1239	172	19	and	and	CCONJ
ijassa-1239	172	20	load	load	NOUN
ijassa-1239	172	21	factor	factor	NOUN
ijassa-1239	172	22	a	a	NOUN
ijassa-1239	172	23	)	)	PUNCT
ijassa-1239	172	24	ρ	ρ	PROPN
ijassa-1239	172	25	∈	∈	PROPN
ijassa-1239	173	1	[	[	X
ijassa-1239	173	2	0.15	0.15	NUM
ijassa-1239	173	3	,	,	PUNCT
ijassa-1239	173	4	0.55	0.55	NUM
ijassa-1239	173	5	]	]	PUNCT
ijassa-1239	173	6	;	;	PUNCT
ijassa-1239	173	7	b	b	X
ijassa-1239	173	8	)	)	PUNCT
ijassa-1239	173	9	ρ	ρ	PROPN
ijassa-1239	173	10	∈	∈	PROPN
ijassa-1239	174	1	[	[	X
ijassa-1239	174	2	0.65	0.65	NUM
ijassa-1239	174	3	,	,	PUNCT
ijassa-1239	174	4	0.85	0.85	NUM
ijassa-1239	174	5	]	]	PUNCT
ijassa-1239	174	6	let	let	VERB
ijassa-1239	174	7	us	we	PRON
ijassa-1239	174	8	determine	determine	VERB
ijassa-1239	174	9	the	the	DET
ijassa-1239	174	10	maximum	maximum	ADJ
ijassa-1239	174	11	,	,	PUNCT
ijassa-1239	174	12	minimum	minimum	ADJ
ijassa-1239	174	13	and	and	CCONJ
ijassa-1239	174	14	mean	mean	ADJ
ijassa-1239	174	15	value	value	NOUN
ijassa-1239	174	16	of	of	ADP
ijassa-1239	174	17	the	the	DET
ijassa-1239	174	18	relative	relative	ADJ
ijassa-1239	174	19	approximation	approximation	NOUN
ijassa-1239	174	20	error	error	NOUN
ijassa-1239	174	21	(	(	PUNCT
ijassa-1239	174	22	table	table	NOUN
ijassa-1239	174	23	5.3	5.3	NUM
ijassa-1239	174	24	)	)	PUNCT
ijassa-1239	174	25	.	.	PUNCT
ijassa-1239	175	1	we	we	PRON
ijassa-1239	175	2	will	will	AUX
ijassa-1239	175	3	also	also	ADV
ijassa-1239	175	4	plot	plot	VERB
ijassa-1239	175	5	relative	relative	ADJ
ijassa-1239	175	6	error	error	NOUN
ijassa-1239	175	7	histograms	histogram	NOUN
ijassa-1239	175	8	in	in	ADP
ijassa-1239	175	9	the	the	DET
ijassa-1239	175	10	order	order	NOUN
ijassa-1239	175	11	in	in	ADP
ijassa-1239	175	12	which	which	PRON
ijassa-1239	175	13	k	k	X
ijassa-1239	175	14	,	,	PUNCT
ijassa-1239	175	15	ρ	ρ	PROPN
ijassa-1239	175	16	,	,	PUNCT
ijassa-1239	175	17	and	and	CCONJ
ijassa-1239	175	18	n	n	NUM
ijassa-1239	175	19	values	value	NOUN
ijassa-1239	175	20	are	be	AUX
ijassa-1239	175	21	presented	present	VERB
ijassa-1239	175	22	in	in	ADP
ijassa-1239	175	23	the	the	DET
ijassa-1239	175	24	5.2	5.2	NUM
ijassa-1239	175	25	table	table	NOUN
ijassa-1239	175	26	.	.	PUNCT
ijassa-1239	176	1	98.85	98.85	NUM
ijassa-1239	176	2	%	%	NOUN
ijassa-1239	176	3	of	of	ADP
ijassa-1239	176	4	the	the	DET
ijassa-1239	176	5	mean	mean	ADJ
ijassa-1239	176	6	response	response	NOUN
ijassa-1239	176	7	time	time	NOUN
ijassa-1239	176	8	approximation	approximation	NOUN
ijassa-1239	176	9	table	table	NOUN
ijassa-1239	176	10	5.3	5.3	NUM
ijassa-1239	176	11	.	.	PUNCT
ijassa-1239	177	1	approximation	approximation	NOUN
ijassa-1239	177	2	errors	error	NOUN
ijassa-1239	177	3	of	of	ADP
ijassa-1239	177	4	estimates	estimate	NOUN
ijassa-1239	177	5	of	of	ADP
ijassa-1239	177	6	the	the	DET
ijassa-1239	177	7	mean	mean	ADJ
ijassa-1239	177	8	response	response	NOUN
ijassa-1239	177	9	time	time	NOUN
ijassa-1239	177	10	and	and	CCONJ
ijassa-1239	177	11	its	its	PRON
ijassa-1239	177	12	tail	tail	NOUN
ijassa-1239	177	13	delay	delay	NOUN
ijassa-1239	177	14	for	for	ADP
ijassa-1239	177	15	a	a	DET
ijassa-1239	177	16	system	system	NOUN
ijassa-1239	177	17	with	with	ADP
ijassa-1239	177	18	poisson	poisson	PROPN
ijassa-1239	177	19	input	input	NOUN
ijassa-1239	177	20	,	,	PUNCT
ijassa-1239	177	21	obtained	obtain	VERB
ijassa-1239	177	22	using	use	VERB
ijassa-1239	177	23	a	a	DET
ijassa-1239	177	24	neural	neural	ADJ
ijassa-1239	177	25	network	network	NOUN
ijassa-1239	177	26	on	on	ADP
ijassa-1239	177	27	data	datum	NOUN
ijassa-1239	177	28	sets	set	NOUN
ijassa-1239	177	29	from	from	ADP
ijassa-1239	177	30	the	the	DET
ijassa-1239	177	31	table	table	NOUN
ijassa-1239	177	32	5.2	5.2	NUM
ijassa-1239	177	33	estimated	estimate	VERB
ijassa-1239	177	34	error	error	NOUN
ijassa-1239	177	35	types	type	NOUN
ijassa-1239	177	36	characteristic	characteristic	ADJ
ijassa-1239	177	37	maximum	maximum	ADJ
ijassa-1239	177	38	pe	pe	PROPN
ijassa-1239	177	39	,	,	PUNCT
ijassa-1239	177	40	%	%	NOUN
ijassa-1239	177	41	minimum	minimum	ADJ
ijassa-1239	177	42	pe	pe	PROPN
ijassa-1239	177	43	,	,	PUNCT
ijassa-1239	177	44	%	%	NOUN
ijassa-1239	177	45	mape	mape	NOUN
ijassa-1239	177	46	,	,	PUNCT
ijassa-1239	177	47	%	%	INTJ
ijassa-1239	177	48	e[rk	e[rk	X
ijassa-1239	177	49	]	]	X
ijassa-1239	177	50	,	,	PUNCT
ijassa-1239	177	51	ρ	ρ	PROPN
ijassa-1239	177	52	∈	∈	PROPN
ijassa-1239	178	1	[	[	X
ijassa-1239	178	2	0.15	0.15	NUM
ijassa-1239	178	3	,	,	PUNCT
ijassa-1239	178	4	0.55	0.55	NUM
ijassa-1239	178	5	]	]	PUNCT
ijassa-1239	178	6	5.61689	5.61689	NUM
ijassa-1239	178	7	0.02737	0.02737	NUM
ijassa-1239	178	8	1.22500	1.22500	NUM
ijassa-1239	178	9	e[rk	e[rk	NOUN
ijassa-1239	178	10	]	]	X
ijassa-1239	178	11	,	,	PUNCT
ijassa-1239	178	12	ρ	ρ	PROPN
ijassa-1239	178	13	∈	∈	PROPN
ijassa-1239	179	1	[	[	X
ijassa-1239	179	2	0.65	0.65	NUM
ijassa-1239	179	3	,	,	PUNCT
ijassa-1239	179	4	0.85	0.85	NUM
ijassa-1239	179	5	]	]	PUNCT
ijassa-1239	179	6	9.93912	9.93912	NUM
ijassa-1239	179	7	0.05324	0.05324	NUM
ijassa-1239	179	8	3.28332	3.28332	NUM
ijassa-1239	179	9	rk(99	rk(99	PROPN
ijassa-1239	179	10	)	)	PUNCT
ijassa-1239	179	11	8.11459	8.11459	NUM
ijassa-1239	179	12	0.00244	0.00244	NUM
ijassa-1239	180	1	1.62527	1.62527	NUM
ijassa-1239	180	2	0	0	NUM
ijassa-1239	180	3	1	1	NUM
ijassa-1239	180	4	2	2	NUM
ijassa-1239	180	5	3	3	NUM
ijassa-1239	180	6	4	4	NUM
ijassa-1239	180	7	5	5	NUM
ijassa-1239	180	8	6	6	NUM
ijassa-1239	180	9	a	a	NOUN
ijassa-1239	180	10	)	)	PUNCT
ijassa-1239	180	11	0	0	NUM
ijassa-1239	181	1	1	1	NUM
ijassa-1239	181	2	2	2	NUM
ijassa-1239	181	3	3	3	NUM
ijassa-1239	181	4	4	4	NUM
ijassa-1239	181	5	5	5	NUM
ijassa-1239	181	6	6	6	NUM
ijassa-1239	181	7	7	7	NUM
ijassa-1239	181	8	8	8	NUM
ijassa-1239	181	9	9	9	NUM
ijassa-1239	181	10	10	10	NUM
ijassa-1239	181	11	b	b	NOUN
ijassa-1239	181	12	)	)	PUNCT
ijassa-1239	181	13	fig	fig	NOUN
ijassa-1239	181	14	.	.	PUNCT
ijassa-1239	182	1	5.4	5.4	NUM
ijassa-1239	182	2	.	.	PUNCT
ijassa-1239	182	3	approximation	approximation	NOUN
ijassa-1239	182	4	errors	error	NOUN
ijassa-1239	182	5	for	for	ADP
ijassa-1239	182	6	the	the	DET
ijassa-1239	182	7	mean	mean	ADJ
ijassa-1239	182	8	response	response	NOUN
ijassa-1239	182	9	time	time	NOUN
ijassa-1239	182	10	of	of	ADP
ijassa-1239	182	11	a	a	DET
ijassa-1239	182	12	system	system	NOUN
ijassa-1239	182	13	with	with	ADP
ijassa-1239	182	14	poisson	poisson	PROPN
ijassa-1239	182	15	input	input	NOUN
ijassa-1239	182	16	,	,	PUNCT
ijassa-1239	182	17	a	a	DET
ijassa-1239	182	18	truncated	truncate	VERB
ijassa-1239	182	19	pareto	pareto	ADJ
ijassa-1239	182	20	distribution	distribution	NOUN
ijassa-1239	182	21	of	of	ADP
ijassa-1239	182	22	service	service	NOUN
ijassa-1239	182	23	time	time	NOUN
ijassa-1239	182	24	and	and	CCONJ
ijassa-1239	182	25	load	load	NOUN
ijassa-1239	182	26	factor	factor	NOUN
ijassa-1239	182	27	a	a	NOUN
ijassa-1239	182	28	)	)	PUNCT
ijassa-1239	182	29	ρ	ρ	PROPN
ijassa-1239	182	30	∈	∈	PROPN
ijassa-1239	183	1	[	[	X
ijassa-1239	183	2	0.15	0.15	NUM
ijassa-1239	183	3	,	,	PUNCT
ijassa-1239	183	4	0.55	0.55	NUM
ijassa-1239	183	5	]	]	PUNCT
ijassa-1239	183	6	;	;	PUNCT
ijassa-1239	183	7	b	b	X
ijassa-1239	183	8	)	)	PUNCT
ijassa-1239	183	9	ρ	ρ	PROPN
ijassa-1239	183	10	∈	∈	PROPN
ijassa-1239	184	1	[	[	X
ijassa-1239	184	2	0.65	0.65	NUM
ijassa-1239	184	3	,	,	PUNCT
ijassa-1239	184	4	0.85	0.85	NUM
ijassa-1239	184	5	]	]	PUNCT
ijassa-1239	184	6	.	.	PUNCT
ijassa-1239	185	1	error	error	NOUN
ijassa-1239	185	2	for	for	ADP
ijassa-1239	185	3	ρ	ρ	PROPN
ijassa-1239	185	4	∈	∈	PROPN
ijassa-1239	185	5	[	[	X
ijassa-1239	185	6	0.15	0.15	NUM
ijassa-1239	185	7	,	,	PUNCT
ijassa-1239	185	8	0.55	0.55	NUM
ijassa-1239	185	9	]	]	PUNCT
ijassa-1239	185	10	does	do	AUX
ijassa-1239	185	11	not	not	PART
ijassa-1239	185	12	exceed	exceed	VERB
ijassa-1239	185	13	3	3	NUM
ijassa-1239	185	14	%	%	NOUN
ijassa-1239	185	15	(	(	PUNCT
ijassa-1239	185	16	fig.5.4a	fig.5.4a	NOUN
ijassa-1239	185	17	)	)	PUNCT
ijassa-1239	185	18	.	.	PUNCT
ijassa-1239	186	1	for	for	ADP
ijassa-1239	186	2	ρ	ρ	PROPN
ijassa-1239	186	3	∈	∈	PROPN
ijassa-1239	186	4	[	[	X
ijassa-1239	186	5	0.65	0.65	NUM
ijassa-1239	186	6	,	,	PUNCT
ijassa-1239	186	7	0.85	0.85	NUM
ijassa-1239	186	8	]	]	PUNCT
ijassa-1239	186	9	,	,	PUNCT
ijassa-1239	186	10	the	the	DET
ijassa-1239	186	11	result	result	NOUN
ijassa-1239	186	12	of	of	ADP
ijassa-1239	186	13	predicting	predict	VERB
ijassa-1239	186	14	the	the	DET
ijassa-1239	186	15	average	average	ADJ
ijassa-1239	186	16	response	response	NOUN
ijassa-1239	186	17	time	time	NOUN
ijassa-1239	186	18	by	by	ADP
ijassa-1239	186	19	the	the	DET
ijassa-1239	186	20	neural	neural	ADJ
ijassa-1239	186	21	network	network	NOUN
ijassa-1239	186	22	turned	turn	VERB
ijassa-1239	186	23	out	out	ADP
ijassa-1239	186	24	to	to	PART
ijassa-1239	186	25	be	be	AUX
ijassa-1239	186	26	somewhat	somewhat	ADV
ijassa-1239	186	27	worse	bad	ADJ
ijassa-1239	186	28	.	.	PUNCT
ijassa-1239	187	1	in	in	ADP
ijassa-1239	187	2	this	this	DET
ijassa-1239	187	3	case	case	NOUN
ijassa-1239	187	4	,	,	PUNCT
ijassa-1239	187	5	the	the	DET
ijassa-1239	187	6	number	number	NOUN
ijassa-1239	187	7	of	of	ADP
ijassa-1239	187	8	approximation	approximation	NOUN
ijassa-1239	187	9	errors	error	NOUN
ijassa-1239	187	10	,	,	PUNCT
ijassa-1239	187	11	which	which	PRON
ijassa-1239	187	12	does	do	AUX
ijassa-1239	187	13	not	not	PART
ijassa-1239	187	14	exceed	exceed	VERB
ijassa-1239	187	15	7	7	NUM
ijassa-1239	187	16	%	%	NOUN
ijassa-1239	187	17	,	,	PUNCT
ijassa-1239	187	18	is	be	AUX
ijassa-1239	187	19	approximately	approximately	ADV
ijassa-1239	187	20	92.27	92.27	NUM
ijassa-1239	187	21	%	%	NOUN
ijassa-1239	187	22	of	of	ADP
ijassa-1239	187	23	their	their	PRON
ijassa-1239	187	24	total	total	ADJ
ijassa-1239	187	25	number	number	NOUN
ijassa-1239	187	26	(	(	PUNCT
ijassa-1239	187	27	fig.5.4b	fig.5.4b	NOUN
ijassa-1239	187	28	)	)	PUNCT
ijassa-1239	187	29	.	.	PUNCT
ijassa-1239	188	1	in	in	ADP
ijassa-1239	188	2	this	this	DET
ijassa-1239	188	3	case	case	NOUN
ijassa-1239	188	4	,	,	PUNCT
ijassa-1239	188	5	the	the	DET
ijassa-1239	188	6	maximum	maximum	ADJ
ijassa-1239	188	7	approximation	approximation	NOUN
ijassa-1239	188	8	error	error	NOUN
ijassa-1239	188	9	does	do	AUX
ijassa-1239	188	10	not	not	PART
ijassa-1239	188	11	exceed	exceed	VERB
ijassa-1239	188	12	10	10	NUM
ijassa-1239	188	13	%	%	NOUN
ijassa-1239	188	14	.	.	PUNCT
ijassa-1239	189	1	for	for	ADP
ijassa-1239	189	2	the	the	DET
ijassa-1239	189	3	99th	99th	ADJ
ijassa-1239	189	4	percentile	percentile	NOUN
ijassa-1239	189	5	of	of	ADP
ijassa-1239	189	6	the	the	DET
ijassa-1239	189	7	response	response	NOUN
ijassa-1239	189	8	time	time	NOUN
ijassa-1239	189	9	distribution	distribution	NOUN
ijassa-1239	189	10	(	(	PUNCT
ijassa-1239	189	11	fig.5.5a	fig.5.5a	NOUN
ijassa-1239	189	12	)	)	PUNCT
ijassa-1239	189	13	,	,	PUNCT
ijassa-1239	189	14	the	the	DET
ijassa-1239	189	15	situation	situation	NOUN
ijassa-1239	189	16	is	be	AUX
ijassa-1239	189	17	such	such	ADJ
ijassa-1239	189	18	that	that	SCONJ
ijassa-1239	189	19	97.54	97.54	NUM
ijassa-1239	189	20	%	%	NOUN
ijassa-1239	189	21	of	of	ADP
ijassa-1239	189	22	the	the	DET
ijassa-1239	189	23	approximation	approximation	NOUN
ijassa-1239	189	24	errors	error	NOUN
ijassa-1239	189	25	do	do	AUX
ijassa-1239	189	26	not	not	PART
ijassa-1239	189	27	exceed	exceed	VERB
ijassa-1239	189	28	5	5	NUM
ijassa-1239	189	29	%	%	NOUN
ijassa-1239	189	30	(	(	PUNCT
ijassa-1239	189	31	fig.5.5b	fig.5.5b	ADJ
ijassa-1239	189	32	)	)	PUNCT
ijassa-1239	189	33	.	.	PUNCT
ijassa-1239	190	1	now	now	ADV
ijassa-1239	190	2	let	let	VERB
ijassa-1239	190	3	’s	’s	NOUN
ijassa-1239	190	4	analyze	analyze	VERB
ijassa-1239	190	5	the	the	DET
ijassa-1239	190	6	case	case	NOUN
ijassa-1239	190	7	with	with	ADP
ijassa-1239	190	8	the	the	DET
ijassa-1239	190	9	erlang	erlang	PROPN
ijassa-1239	190	10	distribution	distribution	NOUN
ijassa-1239	190	11	of	of	ADP
ijassa-1239	190	12	service	service	NOUN
ijassa-1239	190	13	time	time	NOUN
ijassa-1239	190	14	from	from	ADP
ijassa-1239	190	15	(	(	PUNCT
ijassa-1239	190	16	4.2	4.2	NUM
ijassa-1239	190	17	)	)	PUNCT
ijassa-1239	190	18	.	.	PUNCT
ijassa-1239	191	1	to	to	PART
ijassa-1239	191	2	do	do	VERB
ijassa-1239	191	3	this	this	PRON
ijassa-1239	191	4	,	,	PUNCT
ijassa-1239	191	5	consider	consider	VERB
ijassa-1239	191	6	a	a	DET
ijassa-1239	191	7	smaller	small	ADJ
ijassa-1239	191	8	training	training	NOUN
ijassa-1239	191	9	input	input	NOUN
ijassa-1239	191	10	set	set	VERB
ijassa-1239	191	11	from	from	ADP
ijassa-1239	191	12	the	the	DET
ijassa-1239	191	13	5.4	5.4	NUM
ijassa-1239	191	14	table	table	NOUN
ijassa-1239	191	15	.	.	PUNCT
ijassa-1239	192	1	the	the	DET
ijassa-1239	192	2	erlang	erlang	PROPN
ijassa-1239	192	3	distribution	distribution	NOUN
ijassa-1239	192	4	parameter	parameter	NOUN
ijassa-1239	192	5	is	be	AUX
ijassa-1239	192	6	given	give	VERB
ijassa-1239	192	7	by	by	ADP
ijassa-1239	192	8	β	β	X
ijassa-1239	192	9	=	=	SYM
ijassa-1239	192	10	2nρ	2nρ	PROPN
ijassa-1239	192	11	/	/	SYM
ijassa-1239	192	12	b.	b.	PROPN
ijassa-1239	192	13	after	after	ADP
ijassa-1239	192	14	training	train	VERB
ijassa-1239	192	15	the	the	DET
ijassa-1239	192	16	neural	neural	ADJ
ijassa-1239	192	17	network	network	NOUN
ijassa-1239	192	18	,	,	PUNCT
ijassa-1239	192	19	we	we	PRON
ijassa-1239	192	20	build	build	VERB
ijassa-1239	192	21	the	the	DET
ijassa-1239	192	22	corresponding	corresponding	ADJ
ijassa-1239	192	23	copyright	copyright	NOUN
ijassa-1239	192	24	©	©	ADP
ijassa-1239	192	25	2022	2022	NUM
ijassa-1239	192	26	assa	assa	NOUN
ijassa-1239	192	27	.	.	PUNCT
ijassa-1239	193	1	adv	adv	PROPN
ijassa-1239	193	2	syst	syst	PROPN
ijassa-1239	193	3	sci	sci	PROPN
ijassa-1239	193	4	appl	appl	PROPN
ijassa-1239	193	5	(	(	PUNCT
ijassa-1239	193	6	2022	2022	NUM
ijassa-1239	193	7	)	)	PUNCT
ijassa-1239	193	8	78	78	NUM
ijassa-1239	193	9	a.v	a.v	PROPN
ijassa-1239	193	10	.	.	PROPN
ijassa-1239	193	11	gorbunova	gorbunova	PROPN
ijassa-1239	193	12	,	,	PUNCT
ijassa-1239	193	13	v.m	v.m	PROPN
ijassa-1239	193	14	.	.	PROPN
ijassa-1239	193	15	vishnevsky	vishnevsky	PROPN
ijassa-1239	193	16	35	35	NUM
ijassa-1239	193	17	85	85	NUM
ijassa-1239	193	18	135	135	NUM
ijassa-1239	193	19	185	185	NUM
ijassa-1239	193	20	235	235	NUM
ijassa-1239	193	21	285	285	NUM
ijassa-1239	193	22	335	335	NUM
ijassa-1239	193	23	385	385	NUM
ijassa-1239	193	24	435	435	NUM
ijassa-1239	193	25	35	35	NUM
ijassa-1239	193	26	85	85	NUM
ijassa-1239	193	27	135	135	NUM
ijassa-1239	193	28	185	185	NUM
ijassa-1239	193	29	235	235	NUM
ijassa-1239	193	30	285	285	NUM
ijassa-1239	193	31	335	335	NUM
ijassa-1239	193	32	385	385	NUM
ijassa-1239	193	33	435	435	NUM
ijassa-1239	193	34	a	a	DET
ijassa-1239	193	35	n	n	CCONJ
ijassa-1239	193	36	n	n	PRON
ijassa-1239	193	37	simulation	simulation	NOUN
ijassa-1239	193	38	a	a	NOUN
ijassa-1239	193	39	)	)	PUNCT
ijassa-1239	193	40	0	0	NUM
ijassa-1239	193	41	1	1	NUM
ijassa-1239	193	42	2	2	NUM
ijassa-1239	193	43	3	3	NUM
ijassa-1239	193	44	4	4	NUM
ijassa-1239	193	45	5	5	NUM
ijassa-1239	193	46	6	6	NUM
ijassa-1239	193	47	7	7	NUM
ijassa-1239	193	48	8	8	NUM
ijassa-1239	193	49	9	9	NUM
ijassa-1239	193	50	b	b	NOUN
ijassa-1239	193	51	)	)	PUNCT
ijassa-1239	193	52	fig	fig	NOUN
ijassa-1239	193	53	.	.	PUNCT
ijassa-1239	194	1	5.5	5.5	NUM
ijassa-1239	194	2	.	.	PUNCT
ijassa-1239	195	1	for	for	ADP
ijassa-1239	195	2	a	a	DET
ijassa-1239	195	3	system	system	NOUN
ijassa-1239	195	4	with	with	ADP
ijassa-1239	195	5	poisson	poisson	NOUN
ijassa-1239	195	6	input	input	NOUN
ijassa-1239	195	7	and	and	CCONJ
ijassa-1239	195	8	a	a	DET
ijassa-1239	195	9	truncated	truncated	ADJ
ijassa-1239	195	10	pareto	pareto	ADJ
ijassa-1239	195	11	distribution	distribution	NOUN
ijassa-1239	195	12	of	of	ADP
ijassa-1239	195	13	service	service	NOUN
ijassa-1239	195	14	time	time	NOUN
ijassa-1239	195	15	a	a	X
ijassa-1239	195	16	)	)	PUNCT
ijassa-1239	195	17	the	the	DET
ijassa-1239	195	18	99th	99th	ADJ
ijassa-1239	195	19	percentile	percentile	NOUN
ijassa-1239	195	20	of	of	ADP
ijassa-1239	195	21	the	the	DET
ijassa-1239	195	22	response	response	NOUN
ijassa-1239	195	23	time	time	NOUN
ijassa-1239	195	24	distribution	distribution	NOUN
ijassa-1239	195	25	,	,	PUNCT
ijassa-1239	195	26	b	b	X
ijassa-1239	195	27	)	)	PUNCT
ijassa-1239	195	28	approximation	approximation	NOUN
ijassa-1239	195	29	errors	error	NOUN
ijassa-1239	195	30	of	of	ADP
ijassa-1239	195	31	the	the	DET
ijassa-1239	195	32	99th	99th	ADJ
ijassa-1239	195	33	percentile	percentile	ADJ
ijassa-1239	195	34	.	.	PUNCT
ijassa-1239	196	1	table	table	NOUN
ijassa-1239	196	2	5.4	5.4	NUM
ijassa-1239	196	3	.	.	PUNCT
ijassa-1239	197	1	input	input	NOUN
ijassa-1239	197	2	data	datum	NOUN
ijassa-1239	197	3	for	for	ADP
ijassa-1239	197	4	constructing	construct	VERB
ijassa-1239	197	5	estimates	estimate	NOUN
ijassa-1239	197	6	of	of	ADP
ijassa-1239	197	7	the	the	DET
ijassa-1239	197	8	mean	mean	ADJ
ijassa-1239	197	9	response	response	NOUN
ijassa-1239	197	10	time	time	NOUN
ijassa-1239	197	11	and	and	CCONJ
ijassa-1239	197	12	its	its	PRON
ijassa-1239	197	13	tail	tail	NOUN
ijassa-1239	197	14	delay	delay	NOUN
ijassa-1239	197	15	in	in	ADP
ijassa-1239	197	16	the	the	DET
ijassa-1239	197	17	case	case	NOUN
ijassa-1239	197	18	of	of	ADP
ijassa-1239	197	19	the	the	DET
ijassa-1239	197	20	erlang	erlang	PROPN
ijassa-1239	197	21	or	or	CCONJ
ijassa-1239	197	22	gamma	gamma	NOUN
ijassa-1239	197	23	distribution	distribution	NOUN
ijassa-1239	197	24	for	for	ADP
ijassa-1239	197	25	the	the	DET
ijassa-1239	197	26	incoming	incoming	ADJ
ijassa-1239	197	27	flow	flow	NOUN
ijassa-1239	197	28	of	of	ADP
ijassa-1239	197	29	requests	request	NOUN
ijassa-1239	197	30	.	.	PUNCT
ijassa-1239	198	1	no	no	INTJ
ijassa-1239	198	2	.	.	NOUN
ijassa-1239	198	3	1	1	NUM
ijassa-1239	198	4	2	2	NUM
ijassa-1239	198	5	...	...	PUNCT
ijassa-1239	198	6	27	27	NUM
ijassa-1239	198	7	28	28	NUM
ijassa-1239	198	8	29	29	NUM
ijassa-1239	198	9	...	...	PUNCT
ijassa-1239	198	10	405	405	NUM
ijassa-1239	198	11	ρ	ρ	NOUN
ijassa-1239	198	12	0.1	0.1	NUM
ijassa-1239	198	13	0.2	0.2	NUM
ijassa-1239	198	14	...	...	PUNCT
ijassa-1239	199	1	0.9	0.9	NUM
ijassa-1239	199	2	0.1	0.1	NUM
ijassa-1239	199	3	0.2	0.2	NUM
ijassa-1239	199	4	...	...	PUNCT
ijassa-1239	200	1	0.9	0.9	NUM
ijassa-1239	200	2	n	n	NOUN
ijassa-1239	200	3	1	1	NUM
ijassa-1239	200	4	1	1	NUM
ijassa-1239	200	5	...	...	SYM
ijassa-1239	200	6	3	3	NUM
ijassa-1239	200	7	1	1	NUM
ijassa-1239	200	8	1	1	NUM
ijassa-1239	200	9	...	...	SYM
ijassa-1239	200	10	3	3	NUM
ijassa-1239	200	11	k	k	NOUN
ijassa-1239	200	12	2	2	NUM
ijassa-1239	200	13	2	2	NUM
ijassa-1239	200	14	...	...	SYM
ijassa-1239	200	15	2	2	NUM
ijassa-1239	200	16	3	3	NUM
ijassa-1239	200	17	3	3	NUM
ijassa-1239	200	18	...	...	PUNCT
ijassa-1239	200	19	16	16	NUM
ijassa-1239	200	20	estimates	estimate	NOUN
ijassa-1239	200	21	for	for	ADP
ijassa-1239	200	22	the	the	DET
ijassa-1239	200	23	intermediate	intermediate	ADJ
ijassa-1239	200	24	data	datum	NOUN
ijassa-1239	200	25	from	from	ADP
ijassa-1239	200	26	the	the	DET
ijassa-1239	200	27	5.5	5.5	NUM
ijassa-1239	200	28	table	table	NOUN
ijassa-1239	200	29	.	.	PUNCT
ijassa-1239	201	1	so	so	ADV
ijassa-1239	201	2	,	,	PUNCT
ijassa-1239	201	3	for	for	ADP
ijassa-1239	201	4	the	the	DET
ijassa-1239	201	5	mean	mean	ADJ
ijassa-1239	201	6	response	response	NOUN
ijassa-1239	201	7	time	time	NOUN
ijassa-1239	201	8	(	(	PUNCT
ijassa-1239	201	9	fig.5.6a	fig.5.6a	PROPN
ijassa-1239	201	10	)	)	PUNCT
ijassa-1239	201	11	98.51	98.51	NUM
ijassa-1239	201	12	%	%	NOUN
ijassa-1239	201	13	of	of	ADP
ijassa-1239	201	14	errors	error	NOUN
ijassa-1239	201	15	does	do	AUX
ijassa-1239	201	16	not	not	PART
ijassa-1239	201	17	exceed	exceed	VERB
ijassa-1239	201	18	5	5	NUM
ijassa-1239	201	19	%	%	NOUN
ijassa-1239	201	20	(	(	PUNCT
ijassa-1239	201	21	fig.5.7a	fig.5.7a	NOUN
ijassa-1239	201	22	)	)	PUNCT
ijassa-1239	201	23	,	,	PUNCT
ijassa-1239	201	24	and	and	CCONJ
ijassa-1239	201	25	for	for	ADP
ijassa-1239	201	26	its	its	PRON
ijassa-1239	201	27	tail	tail	NOUN
ijassa-1239	201	28	delay	delay	NOUN
ijassa-1239	201	29	(	(	PUNCT
ijassa-1239	201	30	fig.5.6b	fig.5.6b	NOUN
ijassa-1239	201	31	)	)	PUNCT
ijassa-1239	201	32	,	,	PUNCT
ijassa-1239	201	33	this	this	DET
ijassa-1239	201	34	percentage	percentage	NOUN
ijassa-1239	201	35	is	be	AUX
ijassa-1239	201	36	already	already	ADV
ijassa-1239	201	37	99.40	99.40	NUM
ijassa-1239	201	38	%	%	NOUN
ijassa-1239	201	39	,	,	PUNCT
ijassa-1239	201	40	i.e.	i.e.	X
ijassa-1239	201	41	,	,	PUNCT
ijassa-1239	201	42	for	for	ADP
ijassa-1239	201	43	only	only	ADV
ijassa-1239	201	44	two	two	NUM
ijassa-1239	201	45	predictive	predictive	ADJ
ijassa-1239	201	46	values	value	NOUN
ijassa-1239	201	47	,	,	PUNCT
ijassa-1239	201	48	the	the	DET
ijassa-1239	201	49	relative	relative	ADJ
ijassa-1239	201	50	error	error	NOUN
ijassa-1239	201	51	ranges	range	VERB
ijassa-1239	201	52	from	from	ADP
ijassa-1239	201	53	5	5	NUM
ijassa-1239	201	54	%	%	NOUN
ijassa-1239	201	55	to	to	PART
ijassa-1239	201	56	7	7	NUM
ijassa-1239	201	57	%	%	NOUN
ijassa-1239	201	58	(	(	PUNCT
ijassa-1239	201	59	fig.5.7b	fig.5.7b	NOUN
ijassa-1239	201	60	)	)	PUNCT
ijassa-1239	201	61	.	.	PUNCT
ijassa-1239	202	1	the	the	DET
ijassa-1239	202	2	maxima	maxima	PROPN
ijassa-1239	202	3	,	,	PUNCT
ijassa-1239	202	4	minima	minima	PROPN
ijassa-1239	202	5	,	,	PUNCT
ijassa-1239	202	6	and	and	CCONJ
ijassa-1239	202	7	average	average	ADJ
ijassa-1239	202	8	values	value	NOUN
ijassa-1239	202	9	of	of	ADP
ijassa-1239	202	10	the	the	DET
ijassa-1239	202	11	approximation	approximation	NOUN
ijassa-1239	202	12	errors	error	NOUN
ijassa-1239	202	13	are	be	AUX
ijassa-1239	202	14	presented	present	VERB
ijassa-1239	202	15	in	in	ADP
ijassa-1239	202	16	the	the	DET
ijassa-1239	202	17	5.6	5.6	NUM
ijassa-1239	202	18	table	table	NOUN
ijassa-1239	202	19	.	.	PUNCT
ijassa-1239	203	1	the	the	DET
ijassa-1239	203	2	maximum	maximum	ADJ
ijassa-1239	203	3	error	error	NOUN
ijassa-1239	203	4	in	in	ADP
ijassa-1239	203	5	the	the	DET
ijassa-1239	203	6	approximation	approximation	NOUN
ijassa-1239	203	7	of	of	ADP
ijassa-1239	203	8	e[rk	e[rk	PROPN
ijassa-1239	203	9	]	]	PUNCT
ijassa-1239	203	10	and	and	CCONJ
ijassa-1239	203	11	rk(99	rk(99	PROPN
ijassa-1239	203	12	)	)	PUNCT
ijassa-1239	203	13	does	do	AUX
ijassa-1239	203	14	not	not	PART
ijassa-1239	203	15	exceed	exceed	VERB
ijassa-1239	203	16	7.8	7.8	NUM
ijassa-1239	203	17	%	%	NOUN
ijassa-1239	203	18	and	and	CCONJ
ijassa-1239	203	19	6.3	6.3	NUM
ijassa-1239	203	20	%	%	NOUN
ijassa-1239	203	21	,	,	PUNCT
ijassa-1239	203	22	respectively	respectively	ADV
ijassa-1239	203	23	,	,	PUNCT
ijassa-1239	203	24	which	which	PRON
ijassa-1239	203	25	is	be	AUX
ijassa-1239	203	26	acceptable	acceptable	ADJ
ijassa-1239	203	27	,	,	PUNCT
ijassa-1239	203	28	especially	especially	ADV
ijassa-1239	203	29	considering	consider	VERB
ijassa-1239	203	30	that	that	SCONJ
ijassa-1239	203	31	almost	almost	ADV
ijassa-1239	203	32	99	99	NUM
ijassa-1239	203	33	%	%	NOUN
ijassa-1239	203	34	of	of	ADP
ijassa-1239	203	35	the	the	DET
ijassa-1239	203	36	errors	error	NOUN
ijassa-1239	203	37	are	be	AUX
ijassa-1239	203	38	within	within	ADP
ijassa-1239	203	39	5	5	NUM
ijassa-1239	203	40	%	%	NOUN
ijassa-1239	203	41	,	,	PUNCT
ijassa-1239	203	42	which	which	PRON
ijassa-1239	203	43	evidenced	evidence	VERB
ijassa-1239	203	44	by	by	ADP
ijassa-1239	203	45	the	the	DET
ijassa-1239	203	46	low	low	ADJ
ijassa-1239	203	47	values	value	NOUN
ijassa-1239	203	48	of	of	ADP
ijassa-1239	203	49	their	their	PRON
ijassa-1239	203	50	average	average	ADJ
ijassa-1239	203	51	values	value	NOUN
ijassa-1239	203	52	.	.	PUNCT
ijassa-1239	204	1	table	table	NOUN
ijassa-1239	204	2	5.5	5.5	NUM
ijassa-1239	204	3	.	.	PUNCT
ijassa-1239	205	1	intermediate	intermediate	ADJ
ijassa-1239	205	2	input	input	NOUN
ijassa-1239	205	3	data	datum	NOUN
ijassa-1239	205	4	for	for	ADP
ijassa-1239	205	5	constructing	construct	VERB
ijassa-1239	205	6	estimates	estimate	NOUN
ijassa-1239	205	7	of	of	ADP
ijassa-1239	205	8	the	the	DET
ijassa-1239	205	9	mean	mean	ADJ
ijassa-1239	205	10	response	response	NOUN
ijassa-1239	205	11	time	time	NOUN
ijassa-1239	205	12	and	and	CCONJ
ijassa-1239	205	13	its	its	PRON
ijassa-1239	205	14	tail	tail	NOUN
ijassa-1239	205	15	delay	delay	NOUN
ijassa-1239	205	16	in	in	ADP
ijassa-1239	205	17	the	the	DET
ijassa-1239	205	18	case	case	NOUN
ijassa-1239	205	19	of	of	ADP
ijassa-1239	205	20	the	the	DET
ijassa-1239	205	21	erlang	erlang	PROPN
ijassa-1239	205	22	or	or	CCONJ
ijassa-1239	205	23	gamma	gamma	NOUN
ijassa-1239	205	24	distribution	distribution	NOUN
ijassa-1239	205	25	for	for	ADP
ijassa-1239	205	26	the	the	DET
ijassa-1239	205	27	incoming	incoming	ADJ
ijassa-1239	205	28	flow	flow	NOUN
ijassa-1239	205	29	of	of	ADP
ijassa-1239	205	30	requests	request	NOUN
ijassa-1239	205	31	.	.	PUNCT
ijassa-1239	206	1	no	no	INTJ
ijassa-1239	206	2	.	.	NOUN
ijassa-1239	206	3	1	1	NUM
ijassa-1239	206	4	2	2	NUM
ijassa-1239	206	5	...	...	SYM
ijassa-1239	206	6	24	24	NUM
ijassa-1239	206	7	25	25	NUM
ijassa-1239	206	8	26	26	NUM
ijassa-1239	206	9	...	...	PUNCT
ijassa-1239	206	10	336	336	NUM
ijassa-1239	206	11	ρ	ρ	NOUN
ijassa-1239	206	12	0.15	0.15	NUM
ijassa-1239	206	13	0.25	0.25	NUM
ijassa-1239	206	14	...	...	PUNCT
ijassa-1239	207	1	0.85	0.85	NUM
ijassa-1239	207	2	0.15	0.15	NUM
ijassa-1239	207	3	0.25	0.25	NUM
ijassa-1239	207	4	...	...	PUNCT
ijassa-1239	208	1	0.85	0.85	NUM
ijassa-1239	208	2	n	n	CCONJ
ijassa-1239	208	3	1	1	NUM
ijassa-1239	208	4	1	1	NUM
ijassa-1239	208	5	...	...	SYM
ijassa-1239	208	6	3	3	NUM
ijassa-1239	208	7	1	1	NUM
ijassa-1239	208	8	1	1	NUM
ijassa-1239	208	9	...	...	SYM
ijassa-1239	208	10	3	3	NUM
ijassa-1239	208	11	k	k	NOUN
ijassa-1239	208	12	2	2	NUM
ijassa-1239	208	13	2	2	NUM
ijassa-1239	208	14	...	...	SYM
ijassa-1239	208	15	2	2	NUM
ijassa-1239	208	16	3	3	NUM
ijassa-1239	208	17	3	3	NUM
ijassa-1239	208	18	...	...	PUNCT
ijassa-1239	208	19	16	16	NUM
ijassa-1239	208	20	table	table	NOUN
ijassa-1239	208	21	5.6	5.6	NUM
ijassa-1239	208	22	.	.	PUNCT
ijassa-1239	209	1	approximation	approximation	NOUN
ijassa-1239	209	2	errors	error	NOUN
ijassa-1239	209	3	of	of	ADP
ijassa-1239	209	4	estimates	estimate	NOUN
ijassa-1239	209	5	of	of	ADP
ijassa-1239	209	6	the	the	DET
ijassa-1239	209	7	mean	mean	ADJ
ijassa-1239	209	8	response	response	NOUN
ijassa-1239	209	9	time	time	NOUN
ijassa-1239	209	10	and	and	CCONJ
ijassa-1239	209	11	its	its	PRON
ijassa-1239	209	12	tail	tail	NOUN
ijassa-1239	209	13	delay	delay	NOUN
ijassa-1239	209	14	for	for	ADP
ijassa-1239	209	15	a	a	DET
ijassa-1239	209	16	system	system	NOUN
ijassa-1239	209	17	with	with	ADP
ijassa-1239	209	18	an	an	DET
ijassa-1239	209	19	erlang	erlang	NOUN
ijassa-1239	209	20	distribution	distribution	NOUN
ijassa-1239	209	21	of	of	ADP
ijassa-1239	209	22	the	the	DET
ijassa-1239	209	23	incoming	incoming	ADJ
ijassa-1239	209	24	flow	flow	NOUN
ijassa-1239	209	25	,	,	PUNCT
ijassa-1239	209	26	obtained	obtain	VERB
ijassa-1239	209	27	using	use	VERB
ijassa-1239	209	28	a	a	DET
ijassa-1239	209	29	neural	neural	ADJ
ijassa-1239	209	30	network	network	NOUN
ijassa-1239	209	31	on	on	ADP
ijassa-1239	209	32	data	datum	NOUN
ijassa-1239	209	33	sets	set	NOUN
ijassa-1239	209	34	from	from	ADP
ijassa-1239	209	35	the	the	DET
ijassa-1239	209	36	table	table	NOUN
ijassa-1239	209	37	5.5	5.5	NUM
ijassa-1239	209	38	.	.	PUNCT
ijassa-1239	210	1	estimated	estimate	VERB
ijassa-1239	210	2	error	error	NOUN
ijassa-1239	210	3	types	type	NOUN
ijassa-1239	210	4	characteristic	characteristic	ADJ
ijassa-1239	210	5	maximum	maximum	ADJ
ijassa-1239	210	6	pe	pe	PROPN
ijassa-1239	210	7	,	,	PUNCT
ijassa-1239	210	8	%	%	NOUN
ijassa-1239	210	9	minimum	minimum	ADJ
ijassa-1239	210	10	pe	pe	PROPN
ijassa-1239	210	11	,	,	PUNCT
ijassa-1239	210	12	%	%	NOUN
ijassa-1239	210	13	mape	mape	NOUN
ijassa-1239	210	14	,	,	PUNCT
ijassa-1239	210	15	%	%	INTJ
ijassa-1239	210	16	e[rk	e[rk	X
ijassa-1239	210	17	]	]	PUNCT
ijassa-1239	211	1	7.82757	7.82757	NUM
ijassa-1239	211	2	0.00518	0.00518	NUM
ijassa-1239	211	3	1.75565	1.75565	NUM
ijassa-1239	211	4	rk(99	rk(99	NOUN
ijassa-1239	211	5	)	)	PUNCT
ijassa-1239	211	6	6.27911	6.27911	NUM
ijassa-1239	211	7	0.01538	0.01538	NUM
ijassa-1239	211	8	1.55339	1.55339	NUM
ijassa-1239	211	9	if	if	SCONJ
ijassa-1239	211	10	the	the	DET
ijassa-1239	211	11	time	time	NOUN
ijassa-1239	211	12	intervals	interval	NOUN
ijassa-1239	211	13	between	between	ADP
ijassa-1239	211	14	adjacent	adjacent	ADJ
ijassa-1239	211	15	incoming	incoming	ADJ
ijassa-1239	211	16	requests	request	NOUN
ijassa-1239	211	17	have	have	VERB
ijassa-1239	211	18	a	a	DET
ijassa-1239	211	19	gamma	gamma	NOUN
ijassa-1239	211	20	distribution	distribution	NOUN
ijassa-1239	211	21	(	(	PUNCT
ijassa-1239	211	22	4.3	4.3	NUM
ijassa-1239	211	23	)	)	PUNCT
ijassa-1239	211	24	with	with	ADP
ijassa-1239	211	25	parameters	parameter	NOUN
ijassa-1239	211	26	k	k	X
ijassa-1239	211	27	=	=	PUNCT
ijassa-1239	211	28	0.25	0.25	NUM
ijassa-1239	211	29	(	(	PUNCT
ijassa-1239	211	30	cv	cv	PROPN
ijassa-1239	211	31	=	=	SYM
ijassa-1239	211	32	2	2	NUM
ijassa-1239	211	33	)	)	PUNCT
ijassa-1239	211	34	and	and	CCONJ
ijassa-1239	211	35	γ	γ	PROPN
ijassa-1239	211	36	=	=	PUNCT
ijassa-1239	211	37	knρ	knρ	PROPN
ijassa-1239	211	38	/	/	SYM
ijassa-1239	211	39	b	b	NOUN
ijassa-1239	211	40	,	,	PUNCT
ijassa-1239	211	41	then	then	ADV
ijassa-1239	211	42	after	after	ADP
ijassa-1239	211	43	training	train	VERB
ijassa-1239	211	44	the	the	DET
ijassa-1239	211	45	neural	neural	ADJ
ijassa-1239	211	46	network	network	NOUN
ijassa-1239	211	47	on	on	ADP
ijassa-1239	211	48	the	the	DET
ijassa-1239	211	49	input	input	NOUN
ijassa-1239	211	50	data	datum	NOUN
ijassa-1239	211	51	from	from	ADP
ijassa-1239	211	52	the	the	DET
ijassa-1239	211	53	table	table	NOUN
ijassa-1239	211	54	5.4	5.4	NUM
ijassa-1239	211	55	we	we	PRON
ijassa-1239	211	56	get	get	VERB
ijassa-1239	211	57	the	the	DET
ijassa-1239	211	58	following	following	ADJ
ijassa-1239	211	59	result	result	NOUN
ijassa-1239	211	60	for	for	ADP
ijassa-1239	211	61	intermediate	intermediate	ADJ
ijassa-1239	211	62	data	datum	NOUN
ijassa-1239	211	63	from	from	ADP
ijassa-1239	211	64	the	the	DET
ijassa-1239	211	65	table	table	NOUN
ijassa-1239	211	66	5.5	5.5	NUM
ijassa-1239	211	67	.	.	PUNCT
ijassa-1239	212	1	for	for	ADP
ijassa-1239	212	2	the	the	DET
ijassa-1239	212	3	mean	mean	ADJ
ijassa-1239	212	4	response	response	NOUN
ijassa-1239	212	5	time	time	NOUN
ijassa-1239	212	6	(	(	PUNCT
ijassa-1239	212	7	fig.5.8a	fig.5.8a	NOUN
ijassa-1239	212	8	)	)	PUNCT
ijassa-1239	212	9	96.13	96.13	NUM
ijassa-1239	212	10	%	%	NOUN
ijassa-1239	212	11	of	of	ADP
ijassa-1239	212	12	the	the	DET
ijassa-1239	212	13	relative	relative	ADJ
ijassa-1239	212	14	errors	error	NOUN
ijassa-1239	212	15	of	of	ADP
ijassa-1239	212	16	their	their	PRON
ijassa-1239	212	17	total	total	ADJ
ijassa-1239	212	18	number	number	NOUN
ijassa-1239	212	19	does	do	AUX
ijassa-1239	212	20	not	not	PART
ijassa-1239	212	21	exceed	exceed	VERB
ijassa-1239	212	22	6	6	NUM
ijassa-1239	212	23	%	%	NOUN
ijassa-1239	212	24	(	(	PUNCT
ijassa-1239	212	25	fig.5.9a	fig.5.9a	NOUN
ijassa-1239	212	26	)	)	PUNCT
ijassa-1239	212	27	.	.	PUNCT
ijassa-1239	213	1	for	for	ADP
ijassa-1239	213	2	the	the	DET
ijassa-1239	213	3	tail	tail	NOUN
ijassa-1239	213	4	delay	delay	NOUN
ijassa-1239	213	5	(	(	PUNCT
ijassa-1239	213	6	fig.5.8b	fig.5.8b	NOUN
ijassa-1239	213	7	)	)	PUNCT
ijassa-1239	213	8	,	,	PUNCT
ijassa-1239	213	9	the	the	DET
ijassa-1239	213	10	percentage	percentage	NOUN
ijassa-1239	213	11	of	of	ADP
ijassa-1239	213	12	errors	error	NOUN
ijassa-1239	213	13	that	that	PRON
ijassa-1239	213	14	do	do	VERB
ijassa-1239	213	15	copyright	copyright	NOUN
ijassa-1239	213	16	©	©	PROPN
ijassa-1239	213	17	2022	2022	NUM
ijassa-1239	213	18	assa	assa	NOUN
ijassa-1239	213	19	.	.	PUNCT
ijassa-1239	214	1	adv	adv	PROPN
ijassa-1239	214	2	syst	syst	PROPN
ijassa-1239	214	3	sci	sci	PROPN
ijassa-1239	214	4	appl	appl	PROPN
ijassa-1239	214	5	(	(	PUNCT
ijassa-1239	214	6	2022	2022	NUM
ijassa-1239	214	7	)	)	PUNCT
ijassa-1239	214	8	the	the	DET
ijassa-1239	214	9	analysis	analysis	NOUN
ijassa-1239	214	10	of	of	ADP
ijassa-1239	214	11	big	big	ADJ
ijassa-1239	214	12	data	datum	NOUN
ijassa-1239	214	13	centers	center	NOUN
ijassa-1239	214	14	performance	performance	VERB
ijassa-1239	214	15	79	79	NUM
ijassa-1239	214	16	0	0	NUM
ijassa-1239	214	17	20	20	NUM
ijassa-1239	214	18	40	40	NUM
ijassa-1239	214	19	60	60	NUM
ijassa-1239	214	20	80	80	NUM
ijassa-1239	214	21	100	100	NUM
ijassa-1239	214	22	120	120	NUM
ijassa-1239	214	23	140	140	NUM
ijassa-1239	214	24	0	0	NUM
ijassa-1239	214	25	20	20	NUM
ijassa-1239	214	26	40	40	NUM
ijassa-1239	214	27	60	60	NUM
ijassa-1239	214	28	80	80	NUM
ijassa-1239	214	29	100	100	NUM
ijassa-1239	214	30	120	120	NUM
ijassa-1239	214	31	140	140	NUM
ijassa-1239	214	32	a	a	DET
ijassa-1239	214	33	n	n	CCONJ
ijassa-1239	214	34	n	n	PRON
ijassa-1239	214	35	simulation	simulation	NOUN
ijassa-1239	214	36	a	a	NOUN
ijassa-1239	214	37	)	)	PUNCT
ijassa-1239	214	38	35	35	NUM
ijassa-1239	214	39	75	75	NUM
ijassa-1239	214	40	115	115	NUM
ijassa-1239	214	41	155	155	NUM
ijassa-1239	214	42	195	195	NUM
ijassa-1239	214	43	235	235	NUM
ijassa-1239	214	44	275	275	NUM
ijassa-1239	214	45	315	315	NUM
ijassa-1239	214	46	355	355	NUM
ijassa-1239	214	47	35	35	NUM
ijassa-1239	214	48	75	75	NUM
ijassa-1239	214	49	115	115	NUM
ijassa-1239	214	50	155	155	NUM
ijassa-1239	214	51	195	195	NUM
ijassa-1239	214	52	235	235	NUM
ijassa-1239	214	53	275	275	NUM
ijassa-1239	214	54	315	315	NUM
ijassa-1239	214	55	355	355	NUM
ijassa-1239	214	56	a	a	DET
ijassa-1239	214	57	n	n	NUM
ijassa-1239	214	58	n	n	PRON
ijassa-1239	214	59	simulation	simulation	NOUN
ijassa-1239	214	60	b	b	PROPN
ijassa-1239	214	61	)	)	PUNCT
ijassa-1239	214	62	fig	fig	NOUN
ijassa-1239	214	63	.	.	PUNCT
ijassa-1239	215	1	5.6	5.6	NUM
ijassa-1239	215	2	.	.	PUNCT
ijassa-1239	216	1	for	for	ADP
ijassa-1239	216	2	a	a	DET
ijassa-1239	216	3	system	system	NOUN
ijassa-1239	216	4	with	with	ADP
ijassa-1239	216	5	an	an	DET
ijassa-1239	216	6	erlang	erlang	NOUN
ijassa-1239	216	7	distribution	distribution	NOUN
ijassa-1239	216	8	of	of	ADP
ijassa-1239	216	9	the	the	DET
ijassa-1239	216	10	incoming	incoming	ADJ
ijassa-1239	216	11	flow	flow	NOUN
ijassa-1239	216	12	and	and	CCONJ
ijassa-1239	216	13	a	a	DET
ijassa-1239	216	14	truncated	truncated	ADJ
ijassa-1239	216	15	pareto	pareto	ADJ
ijassa-1239	216	16	distribution	distribution	NOUN
ijassa-1239	216	17	of	of	ADP
ijassa-1239	216	18	service	service	NOUN
ijassa-1239	216	19	time	time	NOUN
ijassa-1239	216	20	,	,	PUNCT
ijassa-1239	216	21	a	a	PRON
ijassa-1239	216	22	)	)	PUNCT
ijassa-1239	216	23	the	the	DET
ijassa-1239	216	24	mean	mean	ADJ
ijassa-1239	216	25	response	response	NOUN
ijassa-1239	216	26	time	time	NOUN
ijassa-1239	216	27	,	,	PUNCT
ijassa-1239	216	28	b	b	X
ijassa-1239	216	29	)	)	PUNCT
ijassa-1239	216	30	the	the	DET
ijassa-1239	216	31	99th	99th	ADJ
ijassa-1239	216	32	percentile	percentile	NOUN
ijassa-1239	216	33	of	of	ADP
ijassa-1239	216	34	the	the	DET
ijassa-1239	216	35	response	response	NOUN
ijassa-1239	216	36	time	time	NOUN
ijassa-1239	216	37	distribution	distribution	NOUN
ijassa-1239	216	38	.	.	PUNCT
ijassa-1239	216	39	0	0	NUM
ijassa-1239	216	40	1	1	NUM
ijassa-1239	216	41	2	2	NUM
ijassa-1239	216	42	3	3	NUM
ijassa-1239	216	43	4	4	NUM
ijassa-1239	216	44	5	5	NUM
ijassa-1239	216	45	6	6	NUM
ijassa-1239	216	46	7	7	NUM
ijassa-1239	216	47	8	8	NUM
ijassa-1239	216	48	a	a	NOUN
ijassa-1239	216	49	)	)	PUNCT
ijassa-1239	216	50	0	0	NUM
ijassa-1239	216	51	1	1	NUM
ijassa-1239	216	52	2	2	NUM
ijassa-1239	216	53	3	3	NUM
ijassa-1239	216	54	4	4	NUM
ijassa-1239	216	55	5	5	NUM
ijassa-1239	216	56	6	6	NUM
ijassa-1239	216	57	7	7	NUM
ijassa-1239	216	58	b	b	NOUN
ijassa-1239	216	59	)	)	PUNCT
ijassa-1239	216	60	fig	fig	NOUN
ijassa-1239	216	61	.	.	PUNCT
ijassa-1239	217	1	5.7	5.7	NUM
ijassa-1239	217	2	.	.	PUNCT
ijassa-1239	218	1	system	system	NOUN
ijassa-1239	218	2	approximation	approximation	NOUN
ijassa-1239	218	3	errors	error	NOUN
ijassa-1239	218	4	with	with	ADP
ijassa-1239	218	5	erlang	erlang	NOUN
ijassa-1239	218	6	distribution	distribution	NOUN
ijassa-1239	218	7	of	of	ADP
ijassa-1239	218	8	the	the	DET
ijassa-1239	218	9	incoming	incoming	ADJ
ijassa-1239	218	10	flow	flow	NOUN
ijassa-1239	218	11	and	and	CCONJ
ijassa-1239	218	12	a	a	DET
ijassa-1239	218	13	truncated	truncated	ADJ
ijassa-1239	218	14	pareto	pareto	ADJ
ijassa-1239	218	15	distribution	distribution	NOUN
ijassa-1239	218	16	of	of	ADP
ijassa-1239	218	17	the	the	DET
ijassa-1239	218	18	service	service	NOUN
ijassa-1239	218	19	time	time	NOUN
ijassa-1239	218	20	for	for	ADP
ijassa-1239	218	21	a	a	PRON
ijassa-1239	218	22	)	)	PUNCT
ijassa-1239	218	23	the	the	DET
ijassa-1239	218	24	mean	mean	ADJ
ijassa-1239	218	25	response	response	NOUN
ijassa-1239	218	26	time	time	NOUN
ijassa-1239	218	27	,	,	PUNCT
ijassa-1239	218	28	b	b	X
ijassa-1239	218	29	)	)	PUNCT
ijassa-1239	218	30	the	the	DET
ijassa-1239	218	31	99th	99th	ADJ
ijassa-1239	218	32	percentile	percentile	NOUN
ijassa-1239	218	33	of	of	ADP
ijassa-1239	218	34	the	the	DET
ijassa-1239	218	35	response	response	NOUN
ijassa-1239	218	36	time	time	NOUN
ijassa-1239	218	37	distribution	distribution	NOUN
ijassa-1239	218	38	.	.	PUNCT
ijassa-1239	219	1	not	not	PART
ijassa-1239	219	2	exceed	exceed	VERB
ijassa-1239	219	3	the	the	DET
ijassa-1239	219	4	threshold	threshold	NOUN
ijassa-1239	219	5	of	of	ADP
ijassa-1239	219	6	6	6	NUM
ijassa-1239	219	7	%	%	NOUN
ijassa-1239	219	8	is	be	AUX
ijassa-1239	219	9	94.64	94.64	NUM
ijassa-1239	219	10	%	%	NOUN
ijassa-1239	219	11	(	(	PUNCT
ijassa-1239	219	12	fig.5.9b	fig.5.9b	NOUN
ijassa-1239	219	13	)	)	PUNCT
ijassa-1239	219	14	.	.	PUNCT
ijassa-1239	220	1	in	in	ADP
ijassa-1239	220	2	this	this	DET
ijassa-1239	220	3	case	case	NOUN
ijassa-1239	220	4	,	,	PUNCT
ijassa-1239	220	5	the	the	DET
ijassa-1239	220	6	maximum	maximum	ADJ
ijassa-1239	220	7	relative	relative	ADJ
ijassa-1239	220	8	approximation	approximation	NOUN
ijassa-1239	220	9	error	error	NOUN
ijassa-1239	220	10	does	do	AUX
ijassa-1239	220	11	not	not	PART
ijassa-1239	220	12	exceed	exceed	VERB
ijassa-1239	220	13	9.8	9.8	NUM
ijassa-1239	220	14	%	%	NOUN
ijassa-1239	220	15	in	in	ADP
ijassa-1239	220	16	both	both	DET
ijassa-1239	220	17	cases	case	NOUN
ijassa-1239	220	18	(	(	PUNCT
ijassa-1239	220	19	table	table	NOUN
ijassa-1239	220	20	5.7	5.7	NUM
ijassa-1239	220	21	)	)	PUNCT
ijassa-1239	220	22	.	.	PUNCT
ijassa-1239	221	1	5	5	NUM
ijassa-1239	221	2	45	45	NUM
ijassa-1239	221	3	85	85	NUM
ijassa-1239	221	4	125	125	NUM
ijassa-1239	221	5	165	165	NUM
ijassa-1239	221	6	205	205	NUM
ijassa-1239	221	7	5	5	NUM
ijassa-1239	221	8	45	45	NUM
ijassa-1239	221	9	85	85	NUM
ijassa-1239	221	10	125	125	NUM
ijassa-1239	221	11	165	165	NUM
ijassa-1239	221	12	205	205	NUM
ijassa-1239	221	13	a	a	DET
ijassa-1239	221	14	n	n	NOUN
ijassa-1239	221	15	n	n	PRON
ijassa-1239	221	16	simulation	simulation	NOUN
ijassa-1239	221	17	a	a	NOUN
ijassa-1239	221	18	)	)	PUNCT
ijassa-1239	221	19	30	30	NUM
ijassa-1239	221	20	130	130	NUM
ijassa-1239	221	21	230	230	NUM
ijassa-1239	221	22	330	330	NUM
ijassa-1239	221	23	430	430	NUM
ijassa-1239	221	24	530	530	NUM
ijassa-1239	221	25	630	630	NUM
ijassa-1239	221	26	30	30	NUM
ijassa-1239	221	27	130	130	NUM
ijassa-1239	221	28	230	230	NUM
ijassa-1239	221	29	330	330	NUM
ijassa-1239	221	30	430	430	NUM
ijassa-1239	221	31	530	530	NUM
ijassa-1239	221	32	630	630	NUM
ijassa-1239	221	33	a	a	DET
ijassa-1239	221	34	n	n	NUM
ijassa-1239	221	35	n	n	PRON
ijassa-1239	221	36	simulation	simulation	NOUN
ijassa-1239	221	37	b	b	PROPN
ijassa-1239	221	38	)	)	PUNCT
ijassa-1239	221	39	fig	fig	NOUN
ijassa-1239	221	40	.	.	PUNCT
ijassa-1239	222	1	5.8	5.8	NUM
ijassa-1239	222	2	.	.	X
ijassa-1239	223	1	for	for	ADP
ijassa-1239	223	2	a	a	DET
ijassa-1239	223	3	system	system	NOUN
ijassa-1239	223	4	with	with	ADP
ijassa-1239	223	5	a	a	DET
ijassa-1239	223	6	gamma	gamma	NOUN
ijassa-1239	223	7	distribution	distribution	NOUN
ijassa-1239	223	8	of	of	ADP
ijassa-1239	223	9	the	the	DET
ijassa-1239	223	10	incoming	incoming	ADJ
ijassa-1239	223	11	flow	flow	NOUN
ijassa-1239	223	12	and	and	CCONJ
ijassa-1239	223	13	a	a	DET
ijassa-1239	223	14	truncated	truncated	ADJ
ijassa-1239	223	15	pareto	pareto	ADJ
ijassa-1239	223	16	distribution	distribution	NOUN
ijassa-1239	223	17	of	of	ADP
ijassa-1239	223	18	the	the	DET
ijassa-1239	223	19	service	service	NOUN
ijassa-1239	223	20	time	time	NOUN
ijassa-1239	223	21	a	a	X
ijassa-1239	223	22	)	)	PUNCT
ijassa-1239	223	23	the	the	DET
ijassa-1239	223	24	mean	mean	ADJ
ijassa-1239	223	25	response	response	NOUN
ijassa-1239	223	26	time	time	NOUN
ijassa-1239	223	27	,	,	PUNCT
ijassa-1239	223	28	b	b	X
ijassa-1239	223	29	)	)	PUNCT
ijassa-1239	223	30	the	the	DET
ijassa-1239	223	31	99th	99th	ADJ
ijassa-1239	223	32	percentile	percentile	NOUN
ijassa-1239	223	33	of	of	ADP
ijassa-1239	223	34	the	the	DET
ijassa-1239	223	35	response	response	NOUN
ijassa-1239	223	36	time	time	NOUN
ijassa-1239	223	37	distribution	distribution	NOUN
ijassa-1239	223	38	.	.	PUNCT
ijassa-1239	224	1	if	if	SCONJ
ijassa-1239	224	2	we	we	PRON
ijassa-1239	224	3	analyze	analyze	VERB
ijassa-1239	224	4	the	the	DET
ijassa-1239	224	5	level	level	NOUN
ijassa-1239	224	6	of	of	ADP
ijassa-1239	224	7	load	load	NOUN
ijassa-1239	224	8	reduction	reduction	NOUN
ijassa-1239	224	9	in	in	ADP
ijassa-1239	224	10	case	case	NOUN
ijassa-1239	224	11	of	of	ADP
ijassa-1239	224	12	allocation	allocation	NOUN
ijassa-1239	224	13	of	of	ADP
ijassa-1239	224	14	additional	additional	ADJ
ijassa-1239	224	15	servers	server	NOUN
ijassa-1239	224	16	,	,	PUNCT
ijassa-1239	224	17	then	then	ADV
ijassa-1239	224	18	the	the	DET
ijassa-1239	224	19	situation	situation	NOUN
ijassa-1239	224	20	is	be	AUX
ijassa-1239	224	21	as	as	SCONJ
ijassa-1239	224	22	follows	follow	VERB
ijassa-1239	224	23	.	.	PUNCT
ijassa-1239	225	1	regardless	regardless	ADV
ijassa-1239	225	2	of	of	ADP
ijassa-1239	225	3	the	the	DET
ijassa-1239	225	4	type	type	NOUN
ijassa-1239	225	5	of	of	ADP
ijassa-1239	225	6	distribution	distribution	NOUN
ijassa-1239	225	7	for	for	ADP
ijassa-1239	225	8	the	the	DET
ijassa-1239	225	9	incoming	incoming	ADJ
ijassa-1239	225	10	flow	flow	NOUN
ijassa-1239	225	11	out	out	ADP
ijassa-1239	225	12	of	of	ADP
ijassa-1239	225	13	the	the	DET
ijassa-1239	225	14	three	three	NUM
ijassa-1239	225	15	considered	consider	VERB
ijassa-1239	225	16	,	,	PUNCT
ijassa-1239	225	17	if	if	SCONJ
ijassa-1239	225	18	each	each	DET
ijassa-1239	225	19	node	node	NOUN
ijassa-1239	225	20	has	have	VERB
ijassa-1239	225	21	two	two	NUM
ijassa-1239	225	22	servers	server	NOUN
ijassa-1239	225	23	(	(	PUNCT
ijassa-1239	225	24	n	n	NOUN
ijassa-1239	225	25	=	=	SYM
ijassa-1239	225	26	2	2	NUM
ijassa-1239	225	27	)	)	PUNCT
ijassa-1239	225	28	instead	instead	ADV
ijassa-1239	225	29	of	of	ADP
ijassa-1239	225	30	one	one	NUM
ijassa-1239	225	31	,	,	PUNCT
ijassa-1239	225	32	the	the	DET
ijassa-1239	225	33	mean	mean	ADJ
ijassa-1239	225	34	response	response	NOUN
ijassa-1239	225	35	time	time	NOUN
ijassa-1239	225	36	and	and	CCONJ
ijassa-1239	225	37	tail	tail	NOUN
ijassa-1239	225	38	delay	delay	NOUN
ijassa-1239	225	39	are	be	AUX
ijassa-1239	225	40	approximately	approximately	ADV
ijassa-1239	225	41	halved	halve	VERB
ijassa-1239	225	42	,	,	PUNCT
ijassa-1239	225	43	which	which	PRON
ijassa-1239	225	44	was	be	AUX
ijassa-1239	225	45	expected	expect	VERB
ijassa-1239	225	46	.	.	PUNCT
ijassa-1239	226	1	if	if	SCONJ
ijassa-1239	226	2	the	the	DET
ijassa-1239	226	3	number	number	NOUN
ijassa-1239	226	4	of	of	ADP
ijassa-1239	226	5	servers	server	NOUN
ijassa-1239	226	6	is	be	AUX
ijassa-1239	226	7	n	n	NOUN
ijassa-1239	226	8	=	=	SYM
ijassa-1239	226	9	3	3	NUM
ijassa-1239	226	10	,	,	PUNCT
ijassa-1239	226	11	then	then	ADV
ijassa-1239	226	12	the	the	DET
ijassa-1239	226	13	average	average	ADJ
ijassa-1239	226	14	response	response	NOUN
ijassa-1239	226	15	time	time	NOUN
ijassa-1239	226	16	and	and	CCONJ
ijassa-1239	226	17	its	its	PRON
ijassa-1239	226	18	tail	tail	NOUN
ijassa-1239	226	19	delay	delay	NOUN
ijassa-1239	226	20	are	be	AUX
ijassa-1239	226	21	reduced	reduce	VERB
ijassa-1239	226	22	by	by	ADP
ijassa-1239	226	23	an	an	DET
ijassa-1239	226	24	average	average	NOUN
ijassa-1239	226	25	of	of	ADP
ijassa-1239	226	26	65	65	NUM
ijassa-1239	226	27	%	%	NOUN
ijassa-1239	226	28	compared	compare	VERB
ijassa-1239	226	29	to	to	ADP
ijassa-1239	226	30	n	n	NOUN
ijassa-1239	226	31	=	=	SYM
ijassa-1239	226	32	1	1	NUM
ijassa-1239	226	33	.	.	PUNCT
ijassa-1239	227	1	the	the	DET
ijassa-1239	227	2	calculation	calculation	NOUN
ijassa-1239	227	3	took	take	VERB
ijassa-1239	227	4	place	place	NOUN
ijassa-1239	227	5	for	for	ADP
ijassa-1239	227	6	the	the	DET
ijassa-1239	227	7	high	high	ADJ
ijassa-1239	227	8	load	load	NOUN
ijassa-1239	227	9	level	level	NOUN
ijassa-1239	227	10	ρ	ρ	X
ijassa-1239	227	11	∈	∈	PROPN
ijassa-1239	228	1	[	[	X
ijassa-1239	228	2	0.6	0.6	NUM
ijassa-1239	228	3	,	,	PUNCT
ijassa-1239	228	4	0.9	0.9	NUM
ijassa-1239	228	5	]	]	PUNCT
ijassa-1239	228	6	,	,	PUNCT
ijassa-1239	228	7	since	since	SCONJ
ijassa-1239	228	8	it	it	PRON
ijassa-1239	228	9	copyright	copyright	NOUN
ijassa-1239	228	10	©	©	ADP
ijassa-1239	228	11	2022	2022	NUM
ijassa-1239	228	12	assa	assa	NOUN
ijassa-1239	228	13	.	.	PUNCT
ijassa-1239	229	1	adv	adv	PROPN
ijassa-1239	229	2	syst	syst	PROPN
ijassa-1239	229	3	sci	sci	PROPN
ijassa-1239	229	4	appl	appl	PROPN
ijassa-1239	229	5	(	(	PUNCT
ijassa-1239	229	6	2022	2022	NUM
ijassa-1239	229	7	)	)	PUNCT
ijassa-1239	229	8	80	80	NUM
ijassa-1239	229	9	a.v	a.v	PROPN
ijassa-1239	229	10	.	.	PROPN
ijassa-1239	229	11	gorbunova	gorbunova	PROPN
ijassa-1239	229	12	,	,	PUNCT
ijassa-1239	229	13	v.m	v.m	PROPN
ijassa-1239	229	14	.	.	PUNCT
ijassa-1239	230	1	vishnevsky	vishnevsky	ADJ
ijassa-1239	230	2	0	0	NUM
ijassa-1239	230	3	1	1	NUM
ijassa-1239	230	4	2	2	NUM
ijassa-1239	230	5	3	3	NUM
ijassa-1239	230	6	4	4	NUM
ijassa-1239	230	7	5	5	NUM
ijassa-1239	230	8	6	6	NUM
ijassa-1239	230	9	7	7	NUM
ijassa-1239	230	10	8	8	NUM
ijassa-1239	230	11	9	9	NUM
ijassa-1239	230	12	10	10	NUM
ijassa-1239	230	13	a	a	DET
ijassa-1239	230	14	)	)	PUNCT
ijassa-1239	230	15	0	0	NUM
ijassa-1239	231	1	1	1	NUM
ijassa-1239	231	2	2	2	NUM
ijassa-1239	231	3	3	3	NUM
ijassa-1239	231	4	4	4	NUM
ijassa-1239	231	5	5	5	NUM
ijassa-1239	231	6	6	6	NUM
ijassa-1239	231	7	7	7	NUM
ijassa-1239	231	8	8	8	NUM
ijassa-1239	231	9	9	9	NUM
ijassa-1239	231	10	10	10	NUM
ijassa-1239	231	11	b	b	NOUN
ijassa-1239	231	12	)	)	PUNCT
ijassa-1239	231	13	fig	fig	NOUN
ijassa-1239	231	14	.	.	PUNCT
ijassa-1239	232	1	5.9	5.9	NUM
ijassa-1239	232	2	.	.	PUNCT
ijassa-1239	233	1	system	system	NOUN
ijassa-1239	233	2	approximation	approximation	NOUN
ijassa-1239	233	3	errors	error	NOUN
ijassa-1239	233	4	with	with	ADP
ijassa-1239	233	5	a	a	DET
ijassa-1239	233	6	gamma	gamma	NOUN
ijassa-1239	233	7	distribution	distribution	NOUN
ijassa-1239	233	8	of	of	ADP
ijassa-1239	233	9	the	the	DET
ijassa-1239	233	10	incoming	incoming	ADJ
ijassa-1239	233	11	flow	flow	NOUN
ijassa-1239	233	12	and	and	CCONJ
ijassa-1239	233	13	a	a	DET
ijassa-1239	233	14	truncated	truncated	ADJ
ijassa-1239	233	15	pareto	pareto	ADJ
ijassa-1239	233	16	distribution	distribution	NOUN
ijassa-1239	233	17	of	of	ADP
ijassa-1239	233	18	the	the	DET
ijassa-1239	233	19	service	service	NOUN
ijassa-1239	233	20	time	time	NOUN
ijassa-1239	233	21	for	for	ADP
ijassa-1239	233	22	a	a	PRON
ijassa-1239	233	23	)	)	PUNCT
ijassa-1239	233	24	the	the	DET
ijassa-1239	233	25	mean	mean	ADJ
ijassa-1239	233	26	response	response	NOUN
ijassa-1239	233	27	time	time	NOUN
ijassa-1239	233	28	,	,	PUNCT
ijassa-1239	233	29	b	b	X
ijassa-1239	233	30	)	)	PUNCT
ijassa-1239	233	31	the	the	DET
ijassa-1239	233	32	99th	99th	ADJ
ijassa-1239	233	33	percentile	percentile	NOUN
ijassa-1239	233	34	of	of	ADP
ijassa-1239	233	35	the	the	DET
ijassa-1239	233	36	response	response	NOUN
ijassa-1239	233	37	time	time	NOUN
ijassa-1239	233	38	distribution	distribution	NOUN
ijassa-1239	233	39	.	.	PUNCT
ijassa-1239	234	1	table	table	NOUN
ijassa-1239	234	2	5.7	5.7	NUM
ijassa-1239	234	3	.	.	PUNCT
ijassa-1239	235	1	approximation	approximation	NOUN
ijassa-1239	235	2	errors	error	NOUN
ijassa-1239	235	3	of	of	ADP
ijassa-1239	235	4	estimates	estimate	NOUN
ijassa-1239	235	5	of	of	ADP
ijassa-1239	235	6	the	the	DET
ijassa-1239	235	7	mean	mean	ADJ
ijassa-1239	235	8	response	response	NOUN
ijassa-1239	235	9	time	time	NOUN
ijassa-1239	235	10	and	and	CCONJ
ijassa-1239	235	11	its	its	PRON
ijassa-1239	235	12	tail	tail	NOUN
ijassa-1239	235	13	delay	delay	NOUN
ijassa-1239	235	14	for	for	ADP
ijassa-1239	235	15	a	a	DET
ijassa-1239	235	16	system	system	NOUN
ijassa-1239	235	17	with	with	ADP
ijassa-1239	235	18	a	a	DET
ijassa-1239	235	19	gamma	gamma	NOUN
ijassa-1239	235	20	distribution	distribution	NOUN
ijassa-1239	235	21	of	of	ADP
ijassa-1239	235	22	the	the	DET
ijassa-1239	235	23	incoming	incoming	ADJ
ijassa-1239	235	24	flow	flow	NOUN
ijassa-1239	235	25	,	,	PUNCT
ijassa-1239	235	26	obtained	obtain	VERB
ijassa-1239	235	27	using	use	VERB
ijassa-1239	235	28	a	a	DET
ijassa-1239	235	29	neural	neural	ADJ
ijassa-1239	235	30	network	network	NOUN
ijassa-1239	235	31	on	on	ADP
ijassa-1239	235	32	data	datum	NOUN
ijassa-1239	235	33	sets	set	NOUN
ijassa-1239	235	34	from	from	ADP
ijassa-1239	235	35	the	the	DET
ijassa-1239	235	36	table	table	NOUN
ijassa-1239	235	37	5.5	5.5	NUM
ijassa-1239	235	38	.	.	PUNCT
ijassa-1239	236	1	estimated	estimate	VERB
ijassa-1239	236	2	error	error	NOUN
ijassa-1239	236	3	types	type	NOUN
ijassa-1239	236	4	characteristic	characteristic	ADJ
ijassa-1239	236	5	maximum	maximum	ADJ
ijassa-1239	236	6	pe	pe	PROPN
ijassa-1239	236	7	,	,	PUNCT
ijassa-1239	236	8	%	%	NOUN
ijassa-1239	236	9	minimum	minimum	ADJ
ijassa-1239	236	10	pe	pe	PROPN
ijassa-1239	236	11	,	,	PUNCT
ijassa-1239	236	12	%	%	NOUN
ijassa-1239	236	13	mape	mape	NOUN
ijassa-1239	236	14	,	,	PUNCT
ijassa-1239	236	15	%	%	INTJ
ijassa-1239	236	16	e[rk	e[rk	X
ijassa-1239	236	17	]	]	PUNCT
ijassa-1239	237	1	9.79003	9.79003	NUM
ijassa-1239	237	2	0.00344	0.00344	NUM
ijassa-1239	237	3	2.34142	2.34142	NUM
ijassa-1239	237	4	rk(99	rk(99	PROPN
ijassa-1239	237	5	)	)	PUNCT
ijassa-1239	237	6	9.42462	9.42462	NUM
ijassa-1239	237	7	0.01472	0.01472	NUM
ijassa-1239	237	8	2.31488	2.31488	NUM
ijassa-1239	237	9	is	be	AUX
ijassa-1239	237	10	in	in	ADP
ijassa-1239	237	11	this	this	DET
ijassa-1239	237	12	case	case	NOUN
ijassa-1239	237	13	that	that	SCONJ
ijassa-1239	237	14	the	the	DET
ijassa-1239	237	15	allocation	allocation	NOUN
ijassa-1239	237	16	of	of	ADP
ijassa-1239	237	17	additional	additional	ADJ
ijassa-1239	237	18	resources	resource	NOUN
ijassa-1239	237	19	to	to	PART
ijassa-1239	237	20	improve	improve	VERB
ijassa-1239	237	21	the	the	DET
ijassa-1239	237	22	quality	quality	NOUN
ijassa-1239	237	23	of	of	ADP
ijassa-1239	237	24	service	service	NOUN
ijassa-1239	237	25	is	be	AUX
ijassa-1239	237	26	an	an	DET
ijassa-1239	237	27	urgent	urgent	ADJ
ijassa-1239	237	28	issue	issue	NOUN
ijassa-1239	237	29	.	.	PUNCT
ijassa-1239	238	1	for	for	ADP
ijassa-1239	238	2	clarity	clarity	NOUN
ijassa-1239	238	3	,	,	PUNCT
ijassa-1239	238	4	the	the	DET
ijassa-1239	238	5	figure	figure	NOUN
ijassa-1239	238	6	5.10	5.10	NUM
ijassa-1239	238	7	shows	show	VERB
ijassa-1239	238	8	graphs	graph	NOUN
ijassa-1239	238	9	of	of	ADP
ijassa-1239	238	10	the	the	DET
ijassa-1239	238	11	mean	mean	ADJ
ijassa-1239	238	12	response	response	NOUN
ijassa-1239	238	13	time	time	NOUN
ijassa-1239	238	14	at	at	ADP
ijassa-1239	238	15	a	a	DET
ijassa-1239	238	16	fixed	fixed	ADJ
ijassa-1239	238	17	k	k	NOUN
ijassa-1239	238	18	depending	depend	VERB
ijassa-1239	238	19	on	on	ADP
ijassa-1239	238	20	the	the	DET
ijassa-1239	238	21	load	load	NOUN
ijassa-1239	238	22	level	level	NOUN
ijassa-1239	238	23	for	for	ADP
ijassa-1239	238	24	various	various	ADJ
ijassa-1239	238	25	values	value	NOUN
ijassa-1239	238	26	of	of	ADP
ijassa-1239	238	27	n	n	NOUN
ijassa-1239	238	28	=	=	SYM
ijassa-1239	238	29	1	1	NUM
ijassa-1239	238	30	,	,	PUNCT
ijassa-1239	238	31	2	2	NUM
ijassa-1239	238	32	,	,	PUNCT
ijassa-1239	238	33	3	3	NUM
ijassa-1239	238	34	.	.	NOUN
ijassa-1239	238	35	0	0	NUM
ijassa-1239	238	36	40	40	NUM
ijassa-1239	238	37	80	80	NUM
ijassa-1239	238	38	120	120	NUM
ijassa-1239	238	39	160	160	NUM
ijassa-1239	238	40	200	200	NUM
ijassa-1239	238	41	240	240	NUM
ijassa-1239	238	42	0.1	0.1	NUM
ijassa-1239	238	43	0.2	0.2	NUM
ijassa-1239	238	44	0.3	0.3	NUM
ijassa-1239	238	45	0.4	0.4	NUM
ijassa-1239	238	46	0.5	0.5	NUM
ijassa-1239	238	47	0.6	0.6	NUM
ijassa-1239	238	48	0.7	0.7	NUM
ijassa-1239	238	49	0.8	0.8	NUM
ijassa-1239	238	50	0.9	0.9	NUM
ijassa-1239	238	51	a	a	DET
ijassa-1239	238	52	v	v	NOUN
ijassa-1239	238	53	er	er	INTJ
ijassa-1239	238	54	a	a	DET
ijassa-1239	238	55	g	g	NOUN
ijassa-1239	238	56	e	e	NOUN
ijassa-1239	238	57	re	re	ADP
ijassa-1239	238	58	sp	sp	ADP
ijassa-1239	238	59	o	o	PROPN
ijassa-1239	238	60	n	n	X
ijassa-1239	238	61	se	se	PROPN
ijassa-1239	238	62	t	t	PROPN
ijassa-1239	239	1	i	i	PRON
ijassa-1239	239	2	m	m	PROPN
ijassa-1239	239	3	e	e	NOUN
ijassa-1239	239	4	,	,	PUNCT
ijassa-1239	239	5	m	m	PROPN
ijassa-1239	239	6	s	s	NOUN
ijassa-1239	239	7	load	load	NOUN
ijassa-1239	239	8	1	1	NUM
ijassa-1239	239	9	2	2	NUM
ijassa-1239	239	10	3	3	NUM
ijassa-1239	239	11	a	a	NOUN
ijassa-1239	239	12	)	)	PUNCT
ijassa-1239	239	13	0	0	NUM
ijassa-1239	239	14	40	40	NUM
ijassa-1239	239	15	80	80	NUM
ijassa-1239	239	16	120	120	NUM
ijassa-1239	239	17	160	160	NUM
ijassa-1239	239	18	200	200	NUM
ijassa-1239	239	19	0.1	0.1	NUM
ijassa-1239	239	20	0.2	0.2	NUM
ijassa-1239	239	21	0.3	0.3	NUM
ijassa-1239	239	22	0.4	0.4	NUM
ijassa-1239	239	23	0.5	0.5	NUM
ijassa-1239	239	24	0.6	0.6	NUM
ijassa-1239	239	25	0.7	0.7	NUM
ijassa-1239	239	26	0.8	0.8	NUM
ijassa-1239	239	27	0.9	0.9	NUM
ijassa-1239	239	28	a	a	DET
ijassa-1239	239	29	v	v	NOUN
ijassa-1239	239	30	er	er	INTJ
ijassa-1239	239	31	a	a	DET
ijassa-1239	239	32	g	g	NOUN
ijassa-1239	239	33	e	e	NOUN
ijassa-1239	239	34	re	re	ADP
ijassa-1239	239	35	sp	sp	ADP
ijassa-1239	239	36	o	o	PROPN
ijassa-1239	239	37	n	n	X
ijassa-1239	239	38	se	se	PROPN
ijassa-1239	239	39	t	t	PROPN
ijassa-1239	240	1	i	i	PRON
ijassa-1239	240	2	m	m	PROPN
ijassa-1239	240	3	e	e	NOUN
ijassa-1239	240	4	,	,	PUNCT
ijassa-1239	240	5	m	m	PROPN
ijassa-1239	240	6	s	s	NOUN
ijassa-1239	240	7	load	load	NOUN
ijassa-1239	240	8	1	1	NUM
ijassa-1239	240	9	2	2	NUM
ijassa-1239	240	10	3	3	NUM
ijassa-1239	240	11	b	b	NOUN
ijassa-1239	240	12	)	)	PUNCT
ijassa-1239	240	13	0	0	NUM
ijassa-1239	240	14	40	40	NUM
ijassa-1239	240	15	80	80	NUM
ijassa-1239	240	16	120	120	NUM
ijassa-1239	240	17	160	160	NUM
ijassa-1239	240	18	200	200	NUM
ijassa-1239	240	19	240	240	NUM
ijassa-1239	240	20	280	280	NUM
ijassa-1239	240	21	320	320	NUM
ijassa-1239	240	22	0.1	0.1	NUM
ijassa-1239	240	23	0.2	0.2	NUM
ijassa-1239	240	24	0.3	0.3	NUM
ijassa-1239	240	25	0.4	0.4	NUM
ijassa-1239	240	26	0.5	0.5	NUM
ijassa-1239	240	27	0.6	0.6	NUM
ijassa-1239	240	28	0.7	0.7	NUM
ijassa-1239	240	29	0.8	0.8	NUM
ijassa-1239	240	30	0.9	0.9	NUM
ijassa-1239	240	31	a	a	DET
ijassa-1239	240	32	v	v	NOUN
ijassa-1239	240	33	er	er	INTJ
ijassa-1239	240	34	a	a	DET
ijassa-1239	240	35	g	g	NOUN
ijassa-1239	240	36	e	e	NOUN
ijassa-1239	240	37	re	re	ADP
ijassa-1239	240	38	sp	sp	ADP
ijassa-1239	240	39	o	o	PROPN
ijassa-1239	240	40	n	n	X
ijassa-1239	240	41	se	se	PROPN
ijassa-1239	240	42	t	t	PROPN
ijassa-1239	241	1	i	i	PRON
ijassa-1239	241	2	m	m	PROPN
ijassa-1239	241	3	e	e	NOUN
ijassa-1239	241	4	,	,	PUNCT
ijassa-1239	241	5	m	m	PROPN
ijassa-1239	241	6	s	s	NOUN
ijassa-1239	241	7	load	load	NOUN
ijassa-1239	241	8	1	1	NUM
ijassa-1239	241	9	2	2	NUM
ijassa-1239	241	10	3	3	NUM
ijassa-1239	241	11	c	c	NOUN
ijassa-1239	241	12	)	)	PUNCT
ijassa-1239	241	13	fig	fig	NOUN
ijassa-1239	241	14	.	.	PUNCT
ijassa-1239	242	1	5.10	5.10	NUM
ijassa-1239	242	2	.	.	PUNCT
ijassa-1239	243	1	mean	mean	ADJ
ijassa-1239	243	2	response	response	NOUN
ijassa-1239	243	3	time	time	NOUN
ijassa-1239	243	4	,	,	PUNCT
ijassa-1239	243	5	if	if	SCONJ
ijassa-1239	243	6	the	the	DET
ijassa-1239	243	7	time	time	NOUN
ijassa-1239	243	8	intervals	interval	NOUN
ijassa-1239	243	9	between	between	ADP
ijassa-1239	243	10	adjacent	adjacent	ADJ
ijassa-1239	243	11	incoming	incoming	ADJ
ijassa-1239	243	12	requests	request	NOUN
ijassa-1239	243	13	have	have	VERB
ijassa-1239	243	14	a	a	PRON
ijassa-1239	243	15	)	)	PUNCT
ijassa-1239	243	16	an	an	DET
ijassa-1239	243	17	exponential	exponential	ADJ
ijassa-1239	243	18	distribution	distribution	NOUN
ijassa-1239	243	19	,	,	PUNCT
ijassa-1239	243	20	k	k	PROPN
ijassa-1239	243	21	=	=	SYM
ijassa-1239	243	22	24	24	NUM
ijassa-1239	243	23	,	,	PUNCT
ijassa-1239	243	24	b	b	NOUN
ijassa-1239	243	25	)	)	PUNCT
ijassa-1239	243	26	an	an	DET
ijassa-1239	243	27	erlang	erlang	NOUN
ijassa-1239	243	28	distribution	distribution	NOUN
ijassa-1239	243	29	,	,	PUNCT
ijassa-1239	243	30	k	k	PROPN
ijassa-1239	243	31	=	=	SYM
ijassa-1239	243	32	16	16	NUM
ijassa-1239	243	33	,	,	PUNCT
ijassa-1239	243	34	c	c	NOUN
ijassa-1239	243	35	)	)	PUNCT
ijassa-1239	243	36	a	a	DET
ijassa-1239	243	37	gamma	gamma	NOUN
ijassa-1239	243	38	distribution	distribution	NOUN
ijassa-1239	243	39	,	,	PUNCT
ijassa-1239	243	40	k	k	PROPN
ijassa-1239	243	41	=	=	SYM
ijassa-1239	243	42	16	16	NUM
ijassa-1239	243	43	;	;	PUNCT
ijassa-1239	243	44	1	1	NUM
ijassa-1239	243	45	—	—	PUNCT
ijassa-1239	243	46	n	n	NOUN
ijassa-1239	243	47	=	=	SYM
ijassa-1239	243	48	1	1	NUM
ijassa-1239	243	49	,	,	PUNCT
ijassa-1239	243	50	2	2	NUM
ijassa-1239	243	51	—	—	PUNCT
ijassa-1239	243	52	n	n	NOUN
ijassa-1239	243	53	=	=	SYM
ijassa-1239	243	54	2	2	NUM
ijassa-1239	243	55	,	,	PUNCT
ijassa-1239	243	56	3	3	NUM
ijassa-1239	243	57	—	—	PUNCT
ijassa-1239	243	58	n	n	NOUN
ijassa-1239	243	59	=	=	SYM
ijassa-1239	243	60	3	3	X
ijassa-1239	243	61	.	.	X
ijassa-1239	243	62	summarizing	summarizing	NOUN
ijassa-1239	243	63	,	,	PUNCT
ijassa-1239	243	64	we	we	PRON
ijassa-1239	243	65	can	can	AUX
ijassa-1239	243	66	draw	draw	VERB
ijassa-1239	243	67	the	the	DET
ijassa-1239	243	68	following	following	ADJ
ijassa-1239	243	69	conclusions	conclusion	NOUN
ijassa-1239	243	70	.	.	PUNCT
ijassa-1239	244	1	for	for	ADP
ijassa-1239	244	2	93	93	NUM
ijassa-1239	244	3	%	%	NOUN
ijassa-1239	244	4	of	of	ADP
ijassa-1239	244	5	the	the	DET
ijassa-1239	244	6	input	input	NOUN
ijassa-1239	244	7	data	datum	NOUN
ijassa-1239	244	8	in	in	ADP
ijassa-1239	244	9	the	the	DET
ijassa-1239	244	10	case	case	NOUN
ijassa-1239	244	11	of	of	ADP
ijassa-1239	244	12	an	an	DET
ijassa-1239	244	13	approximation	approximation	NOUN
ijassa-1239	244	14	of	of	ADP
ijassa-1239	244	15	the	the	DET
ijassa-1239	244	16	mean	mean	ADJ
ijassa-1239	244	17	response	response	NOUN
ijassa-1239	244	18	time	time	NOUN
ijassa-1239	244	19	and	and	CCONJ
ijassa-1239	244	20	for	for	ADP
ijassa-1239	244	21	96	96	NUM
ijassa-1239	244	22	%	%	NOUN
ijassa-1239	244	23	of	of	ADP
ijassa-1239	244	24	the	the	DET
ijassa-1239	244	25	data	datum	NOUN
ijassa-1239	244	26	for	for	ADP
ijassa-1239	244	27	the	the	DET
ijassa-1239	244	28	tail	tail	NOUN
ijassa-1239	244	29	delay	delay	NOUN
ijassa-1239	244	30	,	,	PUNCT
ijassa-1239	244	31	the	the	DET
ijassa-1239	244	32	approximation	approximation	NOUN
ijassa-1239	244	33	error	error	NOUN
ijassa-1239	244	34	does	do	AUX
ijassa-1239	244	35	not	not	PART
ijassa-1239	244	36	exceed	exceed	VERB
ijassa-1239	244	37	5	5	NUM
ijassa-1239	244	38	%	%	NOUN
ijassa-1239	244	39	.	.	PUNCT
ijassa-1239	245	1	since	since	SCONJ
ijassa-1239	245	2	we	we	PRON
ijassa-1239	245	3	considered	consider	VERB
ijassa-1239	245	4	the	the	DET
ijassa-1239	245	5	absolute	absolute	ADJ
ijassa-1239	245	6	values	value	NOUN
ijassa-1239	245	7	of	of	ADP
ijassa-1239	245	8	the	the	DET
ijassa-1239	245	9	relative	relative	ADJ
ijassa-1239	245	10	error	error	NOUN
ijassa-1239	245	11	,	,	PUNCT
ijassa-1239	245	12	then	then	ADV
ijassa-1239	245	13	the	the	DET
ijassa-1239	245	14	compensation	compensation	NOUN
ijassa-1239	245	15	of	of	ADP
ijassa-1239	245	16	the	the	DET
ijassa-1239	245	17	approximation	approximation	NOUN
ijassa-1239	245	18	error	error	NOUN
ijassa-1239	245	19	in	in	ADP
ijassa-1239	245	20	the	the	DET
ijassa-1239	245	21	amount	amount	NOUN
ijassa-1239	245	22	of	of	ADP
ijassa-1239	245	23	5	5	NUM
ijassa-1239	245	24	%	%	NOUN
ijassa-1239	245	25	can	can	AUX
ijassa-1239	245	26	,	,	PUNCT
ijassa-1239	245	27	in	in	ADP
ijassa-1239	245	28	the	the	DET
ijassa-1239	245	29	case	case	NOUN
ijassa-1239	245	30	of	of	ADP
ijassa-1239	245	31	positive	positive	ADJ
ijassa-1239	245	32	estimates	estimate	NOUN
ijassa-1239	245	33	,	,	PUNCT
ijassa-1239	245	34	actually	actually	ADV
ijassa-1239	245	35	lead	lead	VERB
ijassa-1239	245	36	to	to	ADP
ijassa-1239	245	37	an	an	DET
ijassa-1239	245	38	overallocation	overallocation	NOUN
ijassa-1239	245	39	of	of	ADP
ijassa-1239	245	40	resources	resource	NOUN
ijassa-1239	245	41	in	in	ADP
ijassa-1239	245	42	the	the	DET
ijassa-1239	245	43	amount	amount	NOUN
ijassa-1239	245	44	of	of	ADP
ijassa-1239	245	45	10	10	NUM
ijassa-1239	245	46	%	%	NOUN
ijassa-1239	245	47	.	.	PUNCT
ijassa-1239	246	1	however	however	ADV
ijassa-1239	246	2	,	,	PUNCT
ijassa-1239	246	3	compared	compare	VERB
ijassa-1239	246	4	to	to	ADP
ijassa-1239	246	5	the	the	DET
ijassa-1239	246	6	50	50	NUM
ijassa-1239	246	7	%	%	NOUN
ijassa-1239	246	8	overprovisioning	overprovisioning	NOUN
ijassa-1239	246	9	of	of	ADP
ijassa-1239	246	10	today	today	NOUN
ijassa-1239	246	11	’s	’s	PART
ijassa-1239	246	12	data	datum	NOUN
ijassa-1239	246	13	centers	center	NOUN
ijassa-1239	246	14	,	,	PUNCT
ijassa-1239	246	15	the	the	DET
ijassa-1239	246	16	40	40	NUM
ijassa-1239	246	17	%	%	NOUN
ijassa-1239	246	18	savings	saving	NOUN
ijassa-1239	246	19	is	be	AUX
ijassa-1239	246	20	a	a	DET
ijassa-1239	246	21	significant	significant	ADJ
ijassa-1239	246	22	benefit	benefit	NOUN
ijassa-1239	246	23	.	.	PUNCT
ijassa-1239	247	1	6	6	X
ijassa-1239	247	2	.	.	X
ijassa-1239	247	3	discussion	discussion	NOUN
ijassa-1239	247	4	now	now	ADV
ijassa-1239	247	5	let	let	VERB
ijassa-1239	247	6	’s	’s	NOUN
ijassa-1239	247	7	analyze	analyze	VERB
ijassa-1239	247	8	the	the	DET
ijassa-1239	247	9	results	result	NOUN
ijassa-1239	247	10	in	in	ADP
ijassa-1239	247	11	more	more	ADJ
ijassa-1239	247	12	detail	detail	NOUN
ijassa-1239	247	13	.	.	PUNCT
ijassa-1239	248	1	the	the	DET
ijassa-1239	248	2	use	use	NOUN
ijassa-1239	248	3	of	of	ADP
ijassa-1239	248	4	neural	neural	ADJ
ijassa-1239	248	5	networks	network	NOUN
ijassa-1239	248	6	as	as	ADP
ijassa-1239	248	7	one	one	NUM
ijassa-1239	248	8	of	of	ADP
ijassa-1239	248	9	the	the	DET
ijassa-1239	248	10	methods	method	NOUN
ijassa-1239	248	11	of	of	ADP
ijassa-1239	248	12	machine	machine	NOUN
ijassa-1239	248	13	learning	learn	VERB
ijassa-1239	248	14	for	for	ADP
ijassa-1239	248	15	predicting	predict	VERB
ijassa-1239	248	16	the	the	DET
ijassa-1239	248	17	mean	mean	ADJ
ijassa-1239	248	18	response	response	NOUN
ijassa-1239	248	19	time	time	NOUN
ijassa-1239	248	20	and	and	CCONJ
ijassa-1239	248	21	its	its	PRON
ijassa-1239	248	22	tail	tail	NOUN
ijassa-1239	248	23	delay	delay	NOUN
ijassa-1239	248	24	makes	make	VERB
ijassa-1239	248	25	it	it	PRON
ijassa-1239	248	26	possible	possible	ADJ
ijassa-1239	248	27	to	to	PART
ijassa-1239	248	28	obtain	obtain	VERB
ijassa-1239	248	29	qualitative	qualitative	ADJ
ijassa-1239	248	30	estimates	estimate	NOUN
ijassa-1239	248	31	without	without	ADP
ijassa-1239	248	32	any	any	DET
ijassa-1239	248	33	restrictions	restriction	NOUN
ijassa-1239	248	34	on	on	ADP
ijassa-1239	248	35	the	the	DET
ijassa-1239	248	36	structure	structure	NOUN
ijassa-1239	248	37	of	of	ADP
ijassa-1239	248	38	the	the	DET
ijassa-1239	248	39	system	system	NOUN
ijassa-1239	248	40	copyright	copyright	NOUN
ijassa-1239	248	41	©	©	ADP
ijassa-1239	248	42	2022	2022	NUM
ijassa-1239	248	43	assa	assa	NOUN
ijassa-1239	248	44	.	.	PUNCT
ijassa-1239	249	1	adv	adv	PROPN
ijassa-1239	249	2	syst	syst	PROPN
ijassa-1239	249	3	sci	sci	PROPN
ijassa-1239	249	4	appl	appl	PROPN
ijassa-1239	249	5	(	(	PUNCT
ijassa-1239	249	6	2022	2022	NUM
ijassa-1239	249	7	)	)	PUNCT
ijassa-1239	249	8	the	the	DET
ijassa-1239	249	9	analysis	analysis	NOUN
ijassa-1239	249	10	of	of	ADP
ijassa-1239	249	11	big	big	ADJ
ijassa-1239	249	12	data	datum	NOUN
ijassa-1239	249	13	centers	center	NOUN
ijassa-1239	249	14	performance	performance	NOUN
ijassa-1239	249	15	81	81	NUM
ijassa-1239	249	16	being	be	AUX
ijassa-1239	249	17	modeled	model	VERB
ijassa-1239	249	18	.	.	PUNCT
ijassa-1239	250	1	this	this	PRON
ijassa-1239	250	2	is	be	AUX
ijassa-1239	250	3	one	one	NUM
ijassa-1239	250	4	of	of	ADP
ijassa-1239	250	5	the	the	DET
ijassa-1239	250	6	main	main	ADJ
ijassa-1239	250	7	advantages	advantage	NOUN
ijassa-1239	250	8	of	of	ADP
ijassa-1239	250	9	the	the	DET
ijassa-1239	250	10	proposed	propose	VERB
ijassa-1239	250	11	approach	approach	NOUN
ijassa-1239	250	12	compared	compare	VERB
ijassa-1239	250	13	,	,	PUNCT
ijassa-1239	250	14	for	for	ADP
ijassa-1239	250	15	example	example	NOUN
ijassa-1239	250	16	,	,	PUNCT
ijassa-1239	250	17	with	with	ADP
ijassa-1239	250	18	analytical	analytical	ADJ
ijassa-1239	250	19	methods	method	NOUN
ijassa-1239	250	20	.	.	PUNCT
ijassa-1239	251	1	based	base	VERB
ijassa-1239	251	2	on	on	ADP
ijassa-1239	251	3	the	the	DET
ijassa-1239	251	4	analysis	analysis	NOUN
ijassa-1239	251	5	of	of	ADP
ijassa-1239	251	6	the	the	DET
ijassa-1239	251	7	publications	publication	NOUN
ijassa-1239	251	8	available	available	ADJ
ijassa-1239	251	9	to	to	ADP
ijassa-1239	251	10	date	date	NOUN
ijassa-1239	251	11	,	,	PUNCT
ijassa-1239	251	12	a	a	DET
ijassa-1239	251	13	partial	partial	ADJ
ijassa-1239	251	14	review	review	NOUN
ijassa-1239	251	15	of	of	ADP
ijassa-1239	251	16	which	which	PRON
ijassa-1239	251	17	was	be	AUX
ijassa-1239	251	18	presented	present	VERB
ijassa-1239	251	19	in	in	ADP
ijassa-1239	251	20	this	this	DET
ijassa-1239	251	21	paper	paper	NOUN
ijassa-1239	251	22	,	,	PUNCT
ijassa-1239	251	23	we	we	PRON
ijassa-1239	251	24	can	can	AUX
ijassa-1239	251	25	draw	draw	VERB
ijassa-1239	251	26	the	the	DET
ijassa-1239	251	27	following	follow	VERB
ijassa-1239	251	28	conclusion	conclusion	NOUN
ijassa-1239	251	29	.	.	PUNCT
ijassa-1239	252	1	the	the	DET
ijassa-1239	252	2	use	use	NOUN
ijassa-1239	252	3	of	of	ADP
ijassa-1239	252	4	analytical	analytical	ADJ
ijassa-1239	252	5	methods	method	NOUN
ijassa-1239	252	6	,	,	PUNCT
ijassa-1239	252	7	if	if	SCONJ
ijassa-1239	252	8	possible	possible	ADJ
ijassa-1239	252	9	,	,	PUNCT
ijassa-1239	252	10	is	be	AUX
ijassa-1239	252	11	usually	usually	ADV
ijassa-1239	252	12	effective	effective	ADJ
ijassa-1239	252	13	only	only	ADV
ijassa-1239	252	14	for	for	ADP
ijassa-1239	252	15	certain	certain	ADJ
ijassa-1239	252	16	types	type	NOUN
ijassa-1239	252	17	of	of	ADP
ijassa-1239	252	18	incoming	incoming	ADJ
ijassa-1239	252	19	or	or	CCONJ
ijassa-1239	252	20	serving	serve	VERB
ijassa-1239	252	21	flows	flow	NOUN
ijassa-1239	252	22	or	or	CCONJ
ijassa-1239	252	23	only	only	ADV
ijassa-1239	252	24	for	for	ADP
ijassa-1239	252	25	some	some	DET
ijassa-1239	252	26	areas	area	NOUN
ijassa-1239	252	27	of	of	ADP
ijassa-1239	252	28	the	the	DET
ijassa-1239	252	29	parameters	parameter	NOUN
ijassa-1239	252	30	of	of	ADP
ijassa-1239	252	31	these	these	DET
ijassa-1239	252	32	distributions	distribution	NOUN
ijassa-1239	252	33	and	and	CCONJ
ijassa-1239	252	34	,	,	PUNCT
ijassa-1239	252	35	accordingly	accordingly	ADV
ijassa-1239	252	36	,	,	PUNCT
ijassa-1239	252	37	the	the	DET
ijassa-1239	252	38	level	level	NOUN
ijassa-1239	252	39	of	of	ADP
ijassa-1239	252	40	load	load	NOUN
ijassa-1239	252	41	(	(	PUNCT
ijassa-1239	252	42	high	high	ADJ
ijassa-1239	252	43	or	or	CCONJ
ijassa-1239	252	44	low	low	ADJ
ijassa-1239	252	45	)	)	PUNCT
ijassa-1239	252	46	,	,	PUNCT
ijassa-1239	252	47	and	and	CCONJ
ijassa-1239	252	48	also	also	ADV
ijassa-1239	252	49	limits	limit	VERB
ijassa-1239	252	50	the	the	DET
ijassa-1239	252	51	structure	structure	NOUN
ijassa-1239	252	52	of	of	ADP
ijassa-1239	252	53	the	the	DET
ijassa-1239	252	54	system	system	NOUN
ijassa-1239	252	55	(	(	PUNCT
ijassa-1239	252	56	number	number	NOUN
ijassa-1239	252	57	of	of	ADP
ijassa-1239	252	58	servers	server	NOUN
ijassa-1239	252	59	or	or	CCONJ
ijassa-1239	252	60	buffer	buffer	VERB
ijassa-1239	252	61	capacity	capacity	NOUN
ijassa-1239	252	62	in	in	ADP
ijassa-1239	252	63	subsystems	subsystem	NOUN
ijassa-1239	252	64	)	)	PUNCT
ijassa-1239	252	65	.	.	PUNCT
ijassa-1239	253	1	on	on	ADP
ijassa-1239	253	2	the	the	DET
ijassa-1239	253	3	other	other	ADJ
ijassa-1239	253	4	hand	hand	NOUN
ijassa-1239	253	5	,	,	PUNCT
ijassa-1239	253	6	the	the	DET
ijassa-1239	253	7	use	use	NOUN
ijassa-1239	253	8	of	of	ADP
ijassa-1239	253	9	neural	neural	ADJ
ijassa-1239	253	10	networks	network	NOUN
ijassa-1239	253	11	requires	require	VERB
ijassa-1239	253	12	preliminary	preliminary	ADJ
ijassa-1239	253	13	data	datum	NOUN
ijassa-1239	253	14	preparation	preparation	NOUN
ijassa-1239	253	15	for	for	ADP
ijassa-1239	253	16	its	its	PRON
ijassa-1239	253	17	training	training	NOUN
ijassa-1239	253	18	.	.	PUNCT
ijassa-1239	254	1	in	in	ADP
ijassa-1239	254	2	this	this	DET
ijassa-1239	254	3	case	case	NOUN
ijassa-1239	254	4	,	,	PUNCT
ijassa-1239	254	5	simulation	simulation	NOUN
ijassa-1239	254	6	modeling	modeling	NOUN
ijassa-1239	254	7	was	be	AUX
ijassa-1239	254	8	used	use	VERB
ijassa-1239	254	9	.	.	PUNCT
ijassa-1239	255	1	by	by	ADP
ijassa-1239	255	2	itself	itself	PRON
ijassa-1239	255	3	,	,	PUNCT
ijassa-1239	255	4	simulation	simulation	NOUN
ijassa-1239	255	5	modeling	modeling	NOUN
ijassa-1239	255	6	makes	make	VERB
ijassa-1239	255	7	it	it	PRON
ijassa-1239	255	8	possible	possible	ADJ
ijassa-1239	255	9	to	to	PART
ijassa-1239	255	10	obtain	obtain	VERB
ijassa-1239	255	11	practically	practically	ADV
ijassa-1239	255	12	exact	exact	ADJ
ijassa-1239	255	13	values	value	NOUN
ijassa-1239	255	14	of	of	ADP
ijassa-1239	255	15	the	the	DET
ijassa-1239	255	16	desired	desire	VERB
ijassa-1239	255	17	characteristics	characteristic	NOUN
ijassa-1239	255	18	.	.	PUNCT
ijassa-1239	256	1	however	however	ADV
ijassa-1239	256	2	,	,	PUNCT
ijassa-1239	256	3	it	it	PRON
ijassa-1239	256	4	requires	require	VERB
ijassa-1239	256	5	serious	serious	ADJ
ijassa-1239	256	6	computational	computational	ADJ
ijassa-1239	256	7	resources	resource	NOUN
ijassa-1239	256	8	and	and	CCONJ
ijassa-1239	256	9	time	time	NOUN
ijassa-1239	256	10	costs	cost	NOUN
ijassa-1239	256	11	,	,	PUNCT
ijassa-1239	256	12	so	so	CCONJ
ijassa-1239	256	13	its	its	PRON
ijassa-1239	256	14	use	use	NOUN
ijassa-1239	256	15	in	in	ADP
ijassa-1239	256	16	its	its	PRON
ijassa-1239	256	17	pure	pure	ADJ
ijassa-1239	256	18	form	form	NOUN
ijassa-1239	256	19	is	be	AUX
ijassa-1239	256	20	not	not	PART
ijassa-1239	256	21	rational	rational	ADJ
ijassa-1239	256	22	.	.	PUNCT
ijassa-1239	257	1	machine	machine	NOUN
ijassa-1239	257	2	learning	learning	NOUN
ijassa-1239	257	3	significantly	significantly	ADV
ijassa-1239	257	4	narrows	narrow	VERB
ijassa-1239	257	5	the	the	DET
ijassa-1239	257	6	range	range	NOUN
ijassa-1239	257	7	of	of	ADP
ijassa-1239	257	8	parameters	parameter	NOUN
ijassa-1239	257	9	for	for	ADP
ijassa-1239	257	10	which	which	PRON
ijassa-1239	257	11	simulation	simulation	NOUN
ijassa-1239	257	12	is	be	AUX
ijassa-1239	257	13	required	require	VERB
ijassa-1239	257	14	.	.	PUNCT
ijassa-1239	258	1	due	due	ADP
ijassa-1239	258	2	to	to	ADP
ijassa-1239	258	3	this	this	PRON
ijassa-1239	258	4	,	,	PUNCT
ijassa-1239	258	5	the	the	DET
ijassa-1239	258	6	time	time	NOUN
ijassa-1239	258	7	spent	spend	VERB
ijassa-1239	258	8	on	on	ADP
ijassa-1239	258	9	its	its	PRON
ijassa-1239	258	10	implementation	implementation	NOUN
ijassa-1239	258	11	is	be	AUX
ijassa-1239	258	12	significantly	significantly	ADV
ijassa-1239	258	13	reduced	reduce	VERB
ijassa-1239	258	14	.	.	PUNCT
ijassa-1239	259	1	at	at	ADP
ijassa-1239	259	2	the	the	DET
ijassa-1239	259	3	same	same	ADJ
ijassa-1239	259	4	time	time	NOUN
ijassa-1239	259	5	,	,	PUNCT
ijassa-1239	259	6	after	after	ADP
ijassa-1239	259	7	training	train	VERB
ijassa-1239	259	8	the	the	DET
ijassa-1239	259	9	neural	neural	ADJ
ijassa-1239	259	10	network	network	NOUN
ijassa-1239	259	11	,	,	PUNCT
ijassa-1239	259	12	it	it	PRON
ijassa-1239	259	13	becomes	become	VERB
ijassa-1239	259	14	possible	possible	ADJ
ijassa-1239	259	15	to	to	PART
ijassa-1239	259	16	obtain	obtain	VERB
ijassa-1239	259	17	estimates	estimate	NOUN
ijassa-1239	259	18	of	of	ADP
ijassa-1239	259	19	acceptable	acceptable	ADJ
ijassa-1239	259	20	quality	quality	NOUN
ijassa-1239	259	21	for	for	ADP
ijassa-1239	259	22	any	any	DET
ijassa-1239	259	23	number	number	NOUN
ijassa-1239	259	24	of	of	ADP
ijassa-1239	259	25	intermediate	intermediate	ADJ
ijassa-1239	259	26	values	value	NOUN
ijassa-1239	259	27	of	of	ADP
ijassa-1239	259	28	the	the	DET
ijassa-1239	259	29	input	input	NOUN
ijassa-1239	259	30	parameters	parameter	NOUN
ijassa-1239	259	31	without	without	ADP
ijassa-1239	259	32	any	any	DET
ijassa-1239	259	33	time	time	NOUN
ijassa-1239	259	34	spent	spend	VERB
ijassa-1239	259	35	on	on	ADP
ijassa-1239	259	36	this	this	PRON
ijassa-1239	259	37	.	.	PUNCT
ijassa-1239	260	1	training	training	NOUN
ijassa-1239	260	2	of	of	ADP
ijassa-1239	260	3	neural	neural	ADJ
ijassa-1239	260	4	networks	network	NOUN
ijassa-1239	260	5	aimed	aim	VERB
ijassa-1239	260	6	at	at	ADP
ijassa-1239	260	7	a	a	DET
ijassa-1239	260	8	satisfactory	satisfactory	ADJ
ijassa-1239	260	9	forecast	forecast	NOUN
ijassa-1239	260	10	quality	quality	NOUN
ijassa-1239	260	11	does	do	AUX
ijassa-1239	260	12	not	not	PART
ijassa-1239	260	13	require	require	VERB
ijassa-1239	260	14	too	too	ADV
ijassa-1239	260	15	deep	deep	ADJ
ijassa-1239	260	16	immersion	immersion	NOUN
ijassa-1239	260	17	in	in	ADP
ijassa-1239	260	18	this	this	DET
ijassa-1239	260	19	area	area	NOUN
ijassa-1239	260	20	due	due	ADP
ijassa-1239	260	21	to	to	ADP
ijassa-1239	260	22	the	the	DET
ijassa-1239	260	23	fact	fact	NOUN
ijassa-1239	260	24	that	that	SCONJ
ijassa-1239	260	25	many	many	ADJ
ijassa-1239	260	26	algorithms	algorithm	NOUN
ijassa-1239	260	27	for	for	ADP
ijassa-1239	260	28	their	their	PRON
ijassa-1239	260	29	training	training	NOUN
ijassa-1239	260	30	are	be	AUX
ijassa-1239	260	31	qualitatively	qualitatively	ADV
ijassa-1239	260	32	implemented	implement	VERB
ijassa-1239	260	33	in	in	ADP
ijassa-1239	260	34	various	various	ADJ
ijassa-1239	260	35	computing	compute	VERB
ijassa-1239	260	36	environments	environment	NOUN
ijassa-1239	260	37	,	,	PUNCT
ijassa-1239	260	38	there	there	PRON
ijassa-1239	260	39	are	be	VERB
ijassa-1239	260	40	ready	ready	ADJ
ijassa-1239	260	41	-	-	PUNCT
ijassa-1239	260	42	made	make	VERB
ijassa-1239	260	43	libraries	library	NOUN
ijassa-1239	260	44	,	,	PUNCT
ijassa-1239	260	45	etc	etc	X
ijassa-1239	260	46	.	.	X
ijassa-1239	261	1	nevertheless	nevertheless	ADV
ijassa-1239	261	2	,	,	PUNCT
ijassa-1239	261	3	if	if	SCONJ
ijassa-1239	261	4	it	it	PRON
ijassa-1239	261	5	is	be	AUX
ijassa-1239	261	6	necessary	necessary	ADJ
ijassa-1239	261	7	to	to	PART
ijassa-1239	261	8	obtain	obtain	VERB
ijassa-1239	261	9	more	more	ADV
ijassa-1239	261	10	accurate	accurate	ADJ
ijassa-1239	261	11	forecasts	forecast	NOUN
ijassa-1239	261	12	,	,	PUNCT
ijassa-1239	261	13	for	for	ADP
ijassa-1239	261	14	example	example	NOUN
ijassa-1239	261	15	,	,	PUNCT
ijassa-1239	261	16	in	in	ADP
ijassa-1239	261	17	comparison	comparison	NOUN
ijassa-1239	261	18	with	with	ADP
ijassa-1239	261	19	those	those	PRON
ijassa-1239	261	20	presented	present	VERB
ijassa-1239	261	21	in	in	ADP
ijassa-1239	261	22	this	this	DET
ijassa-1239	261	23	paper	paper	NOUN
ijassa-1239	261	24	,	,	PUNCT
ijassa-1239	261	25	it	it	PRON
ijassa-1239	261	26	is	be	AUX
ijassa-1239	261	27	possible	possible	ADJ
ijassa-1239	261	28	to	to	PART
ijassa-1239	261	29	involve	involve	VERB
ijassa-1239	261	30	relevant	relevant	ADJ
ijassa-1239	261	31	specialists	specialist	NOUN
ijassa-1239	261	32	.	.	PUNCT
ijassa-1239	262	1	among	among	ADP
ijassa-1239	262	2	the	the	DET
ijassa-1239	262	3	many	many	ADJ
ijassa-1239	262	4	listed	list	VERB
ijassa-1239	262	5	advantages	advantage	NOUN
ijassa-1239	262	6	of	of	ADP
ijassa-1239	262	7	the	the	DET
ijassa-1239	262	8	proposed	propose	VERB
ijassa-1239	262	9	approach	approach	NOUN
ijassa-1239	262	10	,	,	PUNCT
ijassa-1239	262	11	it	it	PRON
ijassa-1239	262	12	also	also	ADV
ijassa-1239	262	13	has	have	VERB
ijassa-1239	262	14	some	some	DET
ijassa-1239	262	15	weaknesses	weakness	NOUN
ijassa-1239	262	16	in	in	ADP
ijassa-1239	262	17	the	the	DET
ijassa-1239	262	18	context	context	NOUN
ijassa-1239	262	19	of	of	ADP
ijassa-1239	262	20	making	make	VERB
ijassa-1239	262	21	a	a	DET
ijassa-1239	262	22	decision	decision	NOUN
ijassa-1239	262	23	to	to	PART
ijassa-1239	262	24	allocate	allocate	VERB
ijassa-1239	262	25	additional	additional	ADJ
ijassa-1239	262	26	resources	resource	NOUN
ijassa-1239	262	27	to	to	PART
ijassa-1239	262	28	compensate	compensate	VERB
ijassa-1239	262	29	for	for	ADP
ijassa-1239	262	30	forecast	forecast	NOUN
ijassa-1239	262	31	errors	error	NOUN
ijassa-1239	262	32	.	.	PUNCT
ijassa-1239	263	1	despite	despite	SCONJ
ijassa-1239	263	2	the	the	DET
ijassa-1239	263	3	low	low	ADJ
ijassa-1239	263	4	approximation	approximation	NOUN
ijassa-1239	263	5	error	error	NOUN
ijassa-1239	263	6	,	,	PUNCT
ijassa-1239	263	7	which	which	PRON
ijassa-1239	263	8	on	on	ADP
ijassa-1239	263	9	average	average	ADJ
ijassa-1239	263	10	does	do	AUX
ijassa-1239	263	11	not	not	PART
ijassa-1239	263	12	exceed	exceed	VERB
ijassa-1239	263	13	5	5	NUM
ijassa-1239	263	14	%	%	NOUN
ijassa-1239	263	15	for	for	ADP
ijassa-1239	263	16	90	90	NUM
ijassa-1239	263	17	%	%	NOUN
ijassa-1239	263	18	of	of	ADP
ijassa-1239	263	19	the	the	DET
ijassa-1239	263	20	data	datum	NOUN
ijassa-1239	263	21	,	,	PUNCT
ijassa-1239	263	22	and	and	CCONJ
ijassa-1239	263	23	in	in	ADP
ijassa-1239	263	24	some	some	DET
ijassa-1239	263	25	cases	case	NOUN
ijassa-1239	263	26	even	even	ADV
ijassa-1239	263	27	3	3	NUM
ijassa-1239	263	28	%	%	NOUN
ijassa-1239	263	29	,	,	PUNCT
ijassa-1239	263	30	there	there	PRON
ijassa-1239	263	31	are	be	VERB
ijassa-1239	263	32	still	still	ADV
ijassa-1239	263	33	a	a	DET
ijassa-1239	263	34	small	small	ADJ
ijassa-1239	263	35	number	number	NOUN
ijassa-1239	263	36	of	of	ADP
ijassa-1239	263	37	errors	error	NOUN
ijassa-1239	263	38	that	that	PRON
ijassa-1239	263	39	exceed	exceed	VERB
ijassa-1239	263	40	,	,	PUNCT
ijassa-1239	263	41	although	although	SCONJ
ijassa-1239	263	42	not	not	PART
ijassa-1239	263	43	significantly	significantly	ADV
ijassa-1239	263	44	,	,	PUNCT
ijassa-1239	263	45	these	these	DET
ijassa-1239	263	46	thresholds	threshold	NOUN
ijassa-1239	263	47	.	.	PUNCT
ijassa-1239	264	1	and	and	CCONJ
ijassa-1239	264	2	it	it	PRON
ijassa-1239	264	3	is	be	AUX
ijassa-1239	264	4	impossible	impossible	ADJ
ijassa-1239	264	5	to	to	PART
ijassa-1239	264	6	predict	predict	VERB
ijassa-1239	264	7	in	in	ADP
ijassa-1239	264	8	advance	advance	NOUN
ijassa-1239	264	9	for	for	ADP
ijassa-1239	264	10	which	which	PRON
ijassa-1239	264	11	specific	specific	ADJ
ijassa-1239	264	12	values	value	NOUN
ijassa-1239	264	13	(	(	PUNCT
ijassa-1239	264	14	ranges	range	NOUN
ijassa-1239	264	15	of	of	ADP
ijassa-1239	264	16	values	value	NOUN
ijassa-1239	264	17	)	)	PUNCT
ijassa-1239	264	18	of	of	ADP
ijassa-1239	264	19	the	the	DET
ijassa-1239	264	20	input	input	NOUN
ijassa-1239	264	21	parameters	parameter	NOUN
ijassa-1239	264	22	this	this	PRON
ijassa-1239	264	23	will	will	AUX
ijassa-1239	264	24	happen	happen	VERB
ijassa-1239	264	25	.	.	PUNCT
ijassa-1239	265	1	this	this	DET
ijassa-1239	265	2	fact	fact	NOUN
ijassa-1239	265	3	is	be	AUX
ijassa-1239	265	4	not	not	PART
ijassa-1239	265	5	affected	affect	VERB
ijassa-1239	265	6	by	by	ADP
ijassa-1239	265	7	the	the	DET
ijassa-1239	265	8	type	type	NOUN
ijassa-1239	265	9	of	of	ADP
ijassa-1239	265	10	distribution	distribution	NOUN
ijassa-1239	265	11	,	,	PUNCT
ijassa-1239	265	12	nor	nor	CCONJ
ijassa-1239	265	13	by	by	ADP
ijassa-1239	265	14	its	its	PRON
ijassa-1239	265	15	coefficient	coefficient	NOUN
ijassa-1239	265	16	of	of	ADP
ijassa-1239	265	17	variation	variation	NOUN
ijassa-1239	265	18	,	,	PUNCT
ijassa-1239	265	19	nor	nor	CCONJ
ijassa-1239	265	20	by	by	ADP
ijassa-1239	265	21	the	the	DET
ijassa-1239	265	22	level	level	NOUN
ijassa-1239	265	23	of	of	ADP
ijassa-1239	265	24	loading	loading	NOUN
ijassa-1239	265	25	,	,	PUNCT
ijassa-1239	265	26	etc	etc	X
ijassa-1239	265	27	.	.	X
ijassa-1239	265	28	,	,	PUNCT
ijassa-1239	265	29	as	as	SCONJ
ijassa-1239	265	30	is	be	AUX
ijassa-1239	265	31	the	the	DET
ijassa-1239	265	32	case	case	NOUN
ijassa-1239	265	33	with	with	ADP
ijassa-1239	265	34	approximate	approximate	ADJ
ijassa-1239	265	35	analytical	analytical	ADJ
ijassa-1239	265	36	approaches	approach	NOUN
ijassa-1239	265	37	.	.	PUNCT
ijassa-1239	266	1	the	the	DET
ijassa-1239	266	2	main	main	ADJ
ijassa-1239	266	3	reasons	reason	NOUN
ijassa-1239	266	4	for	for	ADP
ijassa-1239	266	5	this	this	DET
ijassa-1239	266	6	phenomenon	phenomenon	NOUN
ijassa-1239	266	7	,	,	PUNCT
ijassa-1239	266	8	apparently	apparently	ADV
ijassa-1239	266	9	,	,	PUNCT
ijassa-1239	266	10	are	be	AUX
ijassa-1239	266	11	the	the	DET
ijassa-1239	266	12	features	feature	NOUN
ijassa-1239	266	13	of	of	ADP
ijassa-1239	266	14	ann	ann	PROPN
ijassa-1239	266	15	training	training	NOUN
ijassa-1239	266	16	,	,	PUNCT
ijassa-1239	266	17	the	the	DET
ijassa-1239	266	18	algorithm	algorithm	NOUN
ijassa-1239	266	19	chosen	choose	VERB
ijassa-1239	266	20	for	for	ADP
ijassa-1239	266	21	this	this	PRON
ijassa-1239	266	22	,	,	PUNCT
ijassa-1239	266	23	the	the	DET
ijassa-1239	266	24	size	size	NOUN
ijassa-1239	266	25	of	of	ADP
ijassa-1239	266	26	the	the	DET
ijassa-1239	266	27	training	training	NOUN
ijassa-1239	266	28	data	datum	NOUN
ijassa-1239	266	29	set	set	VERB
ijassa-1239	266	30	,	,	PUNCT
ijassa-1239	266	31	the	the	DET
ijassa-1239	266	32	architecture	architecture	NOUN
ijassa-1239	266	33	of	of	ADP
ijassa-1239	266	34	the	the	DET
ijassa-1239	266	35	neural	neural	ADJ
ijassa-1239	266	36	network	network	NOUN
ijassa-1239	266	37	(	(	PUNCT
ijassa-1239	266	38	the	the	DET
ijassa-1239	266	39	number	number	NOUN
ijassa-1239	266	40	of	of	ADP
ijassa-1239	266	41	hidden	hidden	ADJ
ijassa-1239	266	42	layers	layer	NOUN
ijassa-1239	266	43	,	,	PUNCT
ijassa-1239	266	44	the	the	DET
ijassa-1239	266	45	number	number	NOUN
ijassa-1239	266	46	of	of	ADP
ijassa-1239	266	47	neurons	neuron	NOUN
ijassa-1239	266	48	,	,	PUNCT
ijassa-1239	266	49	activation	activation	NOUN
ijassa-1239	266	50	functions	function	NOUN
ijassa-1239	266	51	,	,	PUNCT
ijassa-1239	266	52	etc	etc	X
ijassa-1239	266	53	.	.	X
ijassa-1239	266	54	)	)	PUNCT
ijassa-1239	266	55	.	.	PUNCT
ijassa-1239	267	1	therefore	therefore	ADV
ijassa-1239	267	2	,	,	PUNCT
ijassa-1239	267	3	the	the	DET
ijassa-1239	267	4	continuation	continuation	NOUN
ijassa-1239	267	5	of	of	ADP
ijassa-1239	267	6	research	research	NOUN
ijassa-1239	267	7	in	in	ADP
ijassa-1239	267	8	this	this	DET
ijassa-1239	267	9	direction	direction	NOUN
ijassa-1239	267	10	,	,	PUNCT
ijassa-1239	267	11	aimed	aim	VERB
ijassa-1239	267	12	at	at	ADP
ijassa-1239	267	13	compensating	compensate	VERB
ijassa-1239	267	14	for	for	ADP
ijassa-1239	267	15	this	this	DET
ijassa-1239	267	16	shortcoming	shortcoming	NOUN
ijassa-1239	267	17	,	,	PUNCT
ijassa-1239	267	18	seems	seem	VERB
ijassa-1239	267	19	to	to	PART
ijassa-1239	267	20	be	be	AUX
ijassa-1239	267	21	an	an	DET
ijassa-1239	267	22	urgent	urgent	ADJ
ijassa-1239	267	23	task	task	NOUN
ijassa-1239	267	24	.	.	PUNCT
ijassa-1239	268	1	7	7	X
ijassa-1239	268	2	.	.	X
ijassa-1239	268	3	conclusion	conclusion	NOUN
ijassa-1239	268	4	the	the	DET
ijassa-1239	268	5	paper	paper	NOUN
ijassa-1239	268	6	proposed	propose	VERB
ijassa-1239	268	7	the	the	DET
ijassa-1239	268	8	approach	approach	NOUN
ijassa-1239	268	9	to	to	PART
ijassa-1239	268	10	assess	assess	VERB
ijassa-1239	268	11	the	the	DET
ijassa-1239	268	12	performance	performance	NOUN
ijassa-1239	268	13	of	of	ADP
ijassa-1239	268	14	big	big	ADJ
ijassa-1239	268	15	data	datum	NOUN
ijassa-1239	268	16	processing	processing	NOUN
ijassa-1239	268	17	center	center	NOUN
ijassa-1239	268	18	services	service	NOUN
ijassa-1239	268	19	.	.	PUNCT
ijassa-1239	269	1	using	use	VERB
ijassa-1239	269	2	a	a	DET
ijassa-1239	269	3	combination	combination	NOUN
ijassa-1239	269	4	of	of	ADP
ijassa-1239	269	5	simulation	simulation	NOUN
ijassa-1239	269	6	modeling	modeling	NOUN
ijassa-1239	269	7	with	with	ADP
ijassa-1239	269	8	neural	neural	ADJ
ijassa-1239	269	9	networks	network	NOUN
ijassa-1239	269	10	,	,	PUNCT
ijassa-1239	269	11	estimates	estimate	NOUN
ijassa-1239	269	12	were	be	AUX
ijassa-1239	269	13	obtained	obtain	VERB
ijassa-1239	269	14	for	for	ADP
ijassa-1239	269	15	the	the	DET
ijassa-1239	269	16	mean	mean	ADJ
ijassa-1239	269	17	response	response	NOUN
ijassa-1239	269	18	time	time	NOUN
ijassa-1239	269	19	and	and	CCONJ
ijassa-1239	269	20	its	its	PRON
ijassa-1239	269	21	tail	tail	NOUN
ijassa-1239	269	22	delay	delay	NOUN
ijassa-1239	269	23	(	(	PUNCT
ijassa-1239	269	24	99th	99th	ADJ
ijassa-1239	269	25	percentile	percentile	NOUN
ijassa-1239	269	26	of	of	ADP
ijassa-1239	269	27	the	the	DET
ijassa-1239	269	28	response	response	NOUN
ijassa-1239	269	29	time	time	NOUN
ijassa-1239	269	30	distribution	distribution	NOUN
ijassa-1239	269	31	)	)	PUNCT
ijassa-1239	269	32	.	.	PUNCT
ijassa-1239	270	1	the	the	DET
ijassa-1239	270	2	advantage	advantage	NOUN
ijassa-1239	270	3	of	of	ADP
ijassa-1239	270	4	the	the	DET
ijassa-1239	270	5	approach	approach	NOUN
ijassa-1239	270	6	compared	compare	VERB
ijassa-1239	270	7	to	to	ADP
ijassa-1239	270	8	previously	previously	ADV
ijassa-1239	270	9	known	know	VERB
ijassa-1239	270	10	ones	one	NOUN
ijassa-1239	270	11	is	be	AUX
ijassa-1239	270	12	its	its	PRON
ijassa-1239	270	13	universality	universality	NOUN
ijassa-1239	270	14	,	,	PUNCT
ijassa-1239	270	15	since	since	SCONJ
ijassa-1239	270	16	there	there	PRON
ijassa-1239	270	17	are	be	VERB
ijassa-1239	270	18	no	no	DET
ijassa-1239	270	19	restrictions	restriction	NOUN
ijassa-1239	270	20	on	on	ADP
ijassa-1239	270	21	the	the	DET
ijassa-1239	270	22	architecture	architecture	NOUN
ijassa-1239	270	23	of	of	ADP
ijassa-1239	270	24	fork	fork	NOUN
ijassa-1239	270	25	-	-	PUNCT
ijassa-1239	270	26	join	join	NOUN
ijassa-1239	270	27	systems	system	NOUN
ijassa-1239	270	28	.	.	PUNCT
ijassa-1239	271	1	the	the	DET
ijassa-1239	271	2	speed	speed	NOUN
ijassa-1239	271	3	of	of	ADP
ijassa-1239	271	4	the	the	DET
ijassa-1239	271	5	trained	train	VERB
ijassa-1239	271	6	neural	neural	ADJ
ijassa-1239	271	7	network	network	NOUN
ijassa-1239	271	8	is	be	AUX
ijassa-1239	271	9	comparable	comparable	ADJ
ijassa-1239	271	10	to	to	ADP
ijassa-1239	271	11	performing	perform	VERB
ijassa-1239	271	12	calculations	calculation	NOUN
ijassa-1239	271	13	using	use	VERB
ijassa-1239	271	14	a	a	DET
ijassa-1239	271	15	simple	simple	ADJ
ijassa-1239	271	16	analytical	analytical	ADJ
ijassa-1239	271	17	formula	formula	NOUN
ijassa-1239	271	18	,	,	PUNCT
ijassa-1239	271	19	as	as	SCONJ
ijassa-1239	271	20	opposed	oppose	VERB
ijassa-1239	271	21	to	to	ADP
ijassa-1239	271	22	the	the	DET
ijassa-1239	271	23	existing	exist	VERB
ijassa-1239	271	24	complex	complex	ADJ
ijassa-1239	271	25	computational	computational	ADJ
ijassa-1239	271	26	algorithms	algorithm	NOUN
ijassa-1239	271	27	.	.	PUNCT
ijassa-1239	272	1	at	at	ADP
ijassa-1239	272	2	the	the	DET
ijassa-1239	272	3	same	same	ADJ
ijassa-1239	272	4	time	time	NOUN
ijassa-1239	272	5	,	,	PUNCT
ijassa-1239	272	6	the	the	DET
ijassa-1239	272	7	approximation	approximation	NOUN
ijassa-1239	272	8	quality	quality	NOUN
ijassa-1239	272	9	is	be	AUX
ijassa-1239	272	10	quite	quite	ADV
ijassa-1239	272	11	high	high	ADJ
ijassa-1239	272	12	and	and	CCONJ
ijassa-1239	272	13	does	do	AUX
ijassa-1239	272	14	not	not	PART
ijassa-1239	272	15	depend	depend	VERB
ijassa-1239	272	16	on	on	ADP
ijassa-1239	272	17	the	the	DET
ijassa-1239	272	18	architecture	architecture	NOUN
ijassa-1239	272	19	of	of	ADP
ijassa-1239	272	20	the	the	DET
ijassa-1239	272	21	mathematical	mathematical	ADJ
ijassa-1239	272	22	model	model	NOUN
ijassa-1239	272	23	used	use	VERB
ijassa-1239	272	24	.	.	PUNCT
ijassa-1239	273	1	acknowledgements	acknowledgement	NOUN
ijassa-1239	273	2	the	the	DET
ijassa-1239	273	3	reported	report	VERB
ijassa-1239	273	4	study	study	NOUN
ijassa-1239	273	5	was	be	AUX
ijassa-1239	273	6	obtained	obtain	VERB
ijassa-1239	273	7	within	within	ADP
ijassa-1239	273	8	rfbr	rfbr	ADJ
ijassa-1239	273	9	grant	grant	NOUN
ijassa-1239	273	10	(	(	PUNCT
ijassa-1239	273	11	project	project	VERB
ijassa-1239	273	12	no	no	NOUN
ijassa-1239	273	13	.	.	NOUN
ijassa-1239	273	14	19	19	NUM
ijassa-1239	273	15	-	-	SYM
ijassa-1239	273	16	29	29	NUM
ijassa-1239	273	17	-	-	PUNCT
ijassa-1239	273	18	06043	06043	NUM
ijassa-1239	273	19	)	)	PUNCT
ijassa-1239	273	20	.	.	PUNCT
ijassa-1239	274	1	copyright	copyright	NOUN
ijassa-1239	274	2	©	©	PROPN
ijassa-1239	274	3	2022	2022	NUM
ijassa-1239	274	4	assa	assa	NOUN
ijassa-1239	274	5	.	.	PUNCT
ijassa-1239	275	1	adv	adv	PROPN
ijassa-1239	275	2	syst	syst	PROPN
ijassa-1239	275	3	sci	sci	PROPN
ijassa-1239	275	4	appl	appl	PROPN
ijassa-1239	275	5	(	(	PUNCT
ijassa-1239	275	6	2022	2022	NUM
ijassa-1239	275	7	)	)	PUNCT
ijassa-1239	275	8	82	82	NUM
ijassa-1239	275	9	a.v	a.v	PROPN
ijassa-1239	275	10	.	.	PROPN
ijassa-1239	275	11	gorbunova	gorbunova	PROPN
ijassa-1239	275	12	,	,	PUNCT
ijassa-1239	275	13	v.m	v.m	PROPN
ijassa-1239	275	14	.	.	PUNCT
ijassa-1239	275	15	vishnevsky	vishnevsky	ADJ
ijassa-1239	275	16	references	reference	NOUN
ijassa-1239	275	17	1	1	NUM
ijassa-1239	275	18	.	.	PUNCT
ijassa-1239	275	19	alesawi	alesawi	PROPN
ijassa-1239	275	20	,	,	PUNCT
ijassa-1239	275	21	s.	s.	PROPN
ijassa-1239	275	22	,	,	PUNCT
ijassa-1239	275	23	nguyen	nguyen	PROPN
ijassa-1239	275	24	,	,	PUNCT
ijassa-1239	275	25	m.	m.	NOUN
ijassa-1239	275	26	,	,	PUNCT
ijassa-1239	275	27	che	che	PROPN
ijassa-1239	275	28	,	,	PUNCT
ijassa-1239	275	29	h.	h.	PROPN
ijassa-1239	275	30	&	&	CCONJ
ijassa-1239	275	31	singhal	singhal	PROPN
ijassa-1239	275	32	,	,	PUNCT
ijassa-1239	275	33	a.	a.	NOUN
ijassa-1239	275	34	(	(	PUNCT
ijassa-1239	275	35	2015	2015	NUM
ijassa-1239	275	36	)	)	PUNCT
ijassa-1239	275	37	.	.	PUNCT
ijassa-1239	276	1	tail	tail	NOUN
ijassa-1239	276	2	latency	latency	NOUN
ijassa-1239	276	3	prediction	prediction	NOUN
ijassa-1239	276	4	for	for	ADP
ijassa-1239	276	5	datacenter	datacenter	NOUN
ijassa-1239	276	6	applications	application	NOUN
ijassa-1239	276	7	in	in	ADP
ijassa-1239	276	8	consolidated	consolidated	ADJ
ijassa-1239	276	9	environments	environment	NOUN
ijassa-1239	276	10	,	,	PUNCT
ijassa-1239	276	11	in	in	ADP
ijassa-1239	276	12	proc	proc	NOUN
ijassa-1239	276	13	.	.	PUNCT
ijassa-1239	277	1	ieee	ieee	PROPN
ijassa-1239	277	2	international	international	PROPN
ijassa-1239	277	3	conference	conference	NOUN
ijassa-1239	277	4	on	on	ADP
ijassa-1239	277	5	computing	computing	NOUN
ijassa-1239	277	6	,	,	PUNCT
ijassa-1239	277	7	networking	networking	NOUN
ijassa-1239	277	8	and	and	CCONJ
ijassa-1239	277	9	communications	communication	NOUN
ijassa-1239	277	10	(	(	PUNCT
ijassa-1239	277	11	icnc	icnc	PROPN
ijassa-1239	277	12	)	)	PUNCT
ijassa-1239	277	13	,	,	PUNCT
ijassa-1239	277	14	honolulu	honolulu	PROPN
ijassa-1239	277	15	,	,	PUNCT
ijassa-1239	277	16	hi	hi	PROPN
ijassa-1239	277	17	,	,	PUNCT
ijassa-1239	277	18	usa	usa	PROPN
ijassa-1239	277	19	,	,	PUNCT
ijassa-1239	277	20	265–269	265–269	NUM
ijassa-1239	277	21	.	.	NOUN
ijassa-1239	278	1	2	2	NUM
ijassa-1239	278	2	.	.	X
ijassa-1239	278	3	apache	apache	PROPN
ijassa-1239	278	4	:	:	PUNCT
ijassa-1239	278	5	apache	apache	PROPN
ijassa-1239	278	6	hadoop	hadoop	NOUN
ijassa-1239	278	7	.	.	PUNCT
ijassa-1239	279	1	(	(	PUNCT
ijassa-1239	279	2	2022	2022	NUM
ijassa-1239	279	3	,	,	PUNCT
ijassa-1239	279	4	april	april	PROPN
ijassa-1239	279	5	)	)	PUNCT
ijassa-1239	279	6	.	.	PUNCT
ijassa-1239	280	1	[	[	X
ijassa-1239	280	2	online	online	X
ijassa-1239	280	3	]	]	X
ijassa-1239	280	4	.	.	PUNCT
ijassa-1239	281	1	available	available	ADJ
ijassa-1239	281	2	:	:	PUNCT
ijassa-1239	281	3	https://hadoop.apache.org	https://hadoop.apache.org	PROPN
ijassa-1239	281	4	3	3	X
ijassa-1239	281	5	.	.	PUNCT
ijassa-1239	281	6	apache	apache	NOUN
ijassa-1239	281	7	spark	spark	PROPN
ijassa-1239	281	8	.	.	PUNCT
ijassa-1239	282	1	(	(	PUNCT
ijassa-1239	282	2	2022	2022	NUM
ijassa-1239	282	3	,	,	PUNCT
ijassa-1239	282	4	april	april	PROPN
ijassa-1239	282	5	)	)	PUNCT
ijassa-1239	282	6	.	.	PUNCT
ijassa-1239	283	1	[	[	X
ijassa-1239	283	2	online	online	X
ijassa-1239	283	3	]	]	X
ijassa-1239	283	4	.	.	PUNCT
ijassa-1239	284	1	available	available	ADJ
ijassa-1239	284	2	:	:	PUNCT
ijassa-1239	284	3	https://spark.apache.org	https://spark.apache.org	X
ijassa-1239	284	4	4	4	X
ijassa-1239	284	5	.	.	PUNCT
ijassa-1239	284	6	harchol	harchol	NOUN
ijassa-1239	284	7	-	-	PUNCT
ijassa-1239	284	8	balter	balter	NOUN
ijassa-1239	284	9	,	,	PUNCT
ijassa-1239	284	10	m.	m.	NOUN
ijassa-1239	284	11	(	(	PUNCT
ijassa-1239	284	12	2013	2013	NUM
ijassa-1239	284	13	)	)	PUNCT
ijassa-1239	284	14	.	.	PUNCT
ijassa-1239	285	1	modeling	modeling	NOUN
ijassa-1239	285	2	and	and	CCONJ
ijassa-1239	285	3	design	design	NOUN
ijassa-1239	285	4	of	of	ADP
ijassa-1239	285	5	computer	computer	NOUN
ijassa-1239	285	6	systems	system	NOUN
ijassa-1239	285	7	:	:	PUNCT
ijassa-1239	285	8	queueing	queue	VERB
ijassa-1239	285	9	theory	theory	NOUN
ijassa-1239	285	10	in	in	ADP
ijassa-1239	285	11	action	action	NOUN
ijassa-1239	285	12	.	.	PUNCT
ijassa-1239	286	1	cambridge	cambridge	PROPN
ijassa-1239	286	2	,	,	PUNCT
ijassa-1239	286	3	u.k	u.k	PROPN
ijassa-1239	286	4	.	.	PROPN
ijassa-1239	286	5	:	:	PUNCT
ijassa-1239	287	1	cambridge	cambridge	PROPN
ijassa-1239	287	2	univ	univ	PROPN
ijassa-1239	287	3	.	.	PUNCT
ijassa-1239	288	1	press	press	PROPN
ijassa-1239	288	2	.	.	PUNCT
ijassa-1239	289	1	5	5	X
ijassa-1239	289	2	.	.	X
ijassa-1239	289	3	blake	blake	PROPN
ijassa-1239	289	4	,	,	PUNCT
ijassa-1239	289	5	g.	g.	PROPN
ijassa-1239	289	6	&	&	CCONJ
ijassa-1239	289	7	saidi	saidi	PROPN
ijassa-1239	289	8	,	,	PUNCT
ijassa-1239	289	9	a.	a.	NOUN
ijassa-1239	289	10	g.	g.	PROPN
ijassa-1239	289	11	(	(	PUNCT
ijassa-1239	289	12	2015	2015	NUM
ijassa-1239	289	13	)	)	PUNCT
ijassa-1239	289	14	.	.	PUNCT
ijassa-1239	290	1	where	where	SCONJ
ijassa-1239	290	2	does	do	AUX
ijassa-1239	290	3	the	the	DET
ijassa-1239	290	4	time	time	NOUN
ijassa-1239	290	5	go	go	VERB
ijassa-1239	290	6	?	?	PUNCT
ijassa-1239	291	1	characterizing	characterize	VERB
ijassa-1239	291	2	tail	tail	NOUN
ijassa-1239	291	3	latency	latency	NOUN
ijassa-1239	291	4	in	in	ADP
ijassa-1239	291	5	memcached	memcache	VERB
ijassa-1239	291	6	.	.	PUNCT
ijassa-1239	292	1	in	in	ADP
ijassa-1239	292	2	proc	proc	PROPN
ijassa-1239	292	3	.	.	PUNCT
ijassa-1239	293	1	ieee	ieee	PROPN
ijassa-1239	293	2	international	international	ADJ
ijassa-1239	293	3	symposium	symposium	NOUN
ijassa-1239	293	4	on	on	ADP
ijassa-1239	293	5	performance	performance	NOUN
ijassa-1239	293	6	analysis	analysis	NOUN
ijassa-1239	293	7	of	of	ADP
ijassa-1239	293	8	systems	system	NOUN
ijassa-1239	293	9	and	and	CCONJ
ijassa-1239	293	10	software	software	NOUN
ijassa-1239	293	11	(	(	PUNCT
ijassa-1239	293	12	ispass	ispass	NOUN
ijassa-1239	293	13	)	)	PUNCT
ijassa-1239	293	14	,	,	PUNCT
ijassa-1239	293	15	21–31	21–31	NUM
ijassa-1239	293	16	.	.	PROPN
ijassa-1239	294	1	6	6	NUM
ijassa-1239	294	2	.	.	X
ijassa-1239	295	1	david	david	PROPN
ijassa-1239	295	2	,	,	PUNCT
ijassa-1239	295	3	h.	h.	PROPN
ijassa-1239	295	4	a.	a.	PROPN
ijassa-1239	295	5	&	&	CCONJ
ijassa-1239	295	6	nagaraja	nagaraja	PROPN
ijassa-1239	295	7	h.	h.	PROPN
ijassa-1239	295	8	n.	n.	PROPN
ijassa-1239	295	9	(	(	PUNCT
ijassa-1239	295	10	2003	2003	NUM
ijassa-1239	295	11	)	)	PUNCT
ijassa-1239	295	12	order	order	NOUN
ijassa-1239	295	13	statistics	statistic	NOUN
ijassa-1239	295	14	.	.	PUNCT
ijassa-1239	296	1	hoboken	hoboken	PROPN
ijassa-1239	296	2	,	,	PUNCT
ijassa-1239	296	3	nj	nj	PROPN
ijassa-1239	296	4	:	:	PUNCT
ijassa-1239	296	5	john	john	PROPN
ijassa-1239	296	6	wiley	wiley	PROPN
ijassa-1239	296	7	&	&	CCONJ
ijassa-1239	296	8	sons	son	NOUN
ijassa-1239	296	9	.	.	PUNCT
ijassa-1239	297	1	7	7	X
ijassa-1239	297	2	.	.	X
ijassa-1239	297	3	dean	dean	PROPN
ijassa-1239	297	4	,	,	PUNCT
ijassa-1239	297	5	j.	j.	PROPN
ijassa-1239	297	6	&	&	CCONJ
ijassa-1239	297	7	ghemawat	ghemawat	PROPN
ijassa-1239	297	8	,	,	PUNCT
ijassa-1239	297	9	s.	s.	PROPN
ijassa-1239	297	10	(	(	PUNCT
ijassa-1239	297	11	2004	2004	NUM
ijassa-1239	297	12	)	)	PUNCT
ijassa-1239	297	13	.	.	PUNCT
ijassa-1239	298	1	simplified	simplify	VERB
ijassa-1239	298	2	data	datum	NOUN
ijassa-1239	298	3	processing	processing	NOUN
ijassa-1239	298	4	on	on	ADP
ijassa-1239	298	5	large	large	ADJ
ijassa-1239	298	6	clusters	cluster	NOUN
ijassa-1239	298	7	,	,	PUNCT
ijassa-1239	298	8	in	in	ADP
ijassa-1239	298	9	proc	proc	NOUN
ijassa-1239	298	10	.	.	PUNCT
ijassa-1239	299	1	6th	6th	ADJ
ijassa-1239	299	2	symposium	symposium	NOUN
ijassa-1239	299	3	on	on	ADP
ijassa-1239	299	4	operating	operating	NOUN
ijassa-1239	299	5	systems	system	NOUN
ijassa-1239	299	6	design	design	NOUN
ijassa-1239	299	7	and	and	CCONJ
ijassa-1239	299	8	implementation	implementation	NOUN
ijassa-1239	299	9	(	(	PUNCT
ijassa-1239	299	10	osdi	osdi	NOUN
ijassa-1239	299	11	)	)	PUNCT
ijassa-1239	299	12	,	,	PUNCT
ijassa-1239	299	13	san	san	PROPN
ijassa-1239	299	14	francisco	francisco	PROPN
ijassa-1239	299	15	,	,	PUNCT
ijassa-1239	299	16	ca	ca	NOUN
ijassa-1239	299	17	,	,	PUNCT
ijassa-1239	299	18	137–150	137–150	NUM
ijassa-1239	299	19	.	.	PUNCT
ijassa-1239	299	20	8	8	NUM
ijassa-1239	299	21	.	.	X
ijassa-1239	299	22	gorbunova	gorbunova	PROPN
ijassa-1239	299	23	,	,	PUNCT
ijassa-1239	299	24	a.	a.	PROPN
ijassa-1239	299	25	v.	v.	PROPN
ijassa-1239	299	26	&	&	CCONJ
ijassa-1239	299	27	lebedev	lebedev	PROPN
ijassa-1239	299	28	,	,	PUNCT
ijassa-1239	299	29	a.	a.	PROPN
ijassa-1239	299	30	v.	v.	PROPN
ijassa-1239	299	31	(	(	PUNCT
ijassa-1239	299	32	2020	2020	NUM
ijassa-1239	299	33	)	)	PUNCT
ijassa-1239	299	34	.	.	PUNCT
ijassa-1239	300	1	bivariate	bivariate	ADJ
ijassa-1239	300	2	distributions	distribution	NOUN
ijassa-1239	300	3	of	of	ADP
ijassa-1239	300	4	maximum	maximum	ADJ
ijassa-1239	300	5	remaining	remain	VERB
ijassa-1239	300	6	service	service	NOUN
ijassa-1239	300	7	times	time	NOUN
ijassa-1239	300	8	in	in	ADP
ijassa-1239	300	9	fork	fork	NOUN
ijassa-1239	300	10	-	-	PUNCT
ijassa-1239	300	11	join	join	VERB
ijassa-1239	300	12	infinite	infinite	ADJ
ijassa-1239	300	13	-	-	PUNCT
ijassa-1239	300	14	server	server	NOUN
ijassa-1239	300	15	queues	queue	NOUN
ijassa-1239	300	16	,	,	PUNCT
ijassa-1239	300	17	problems	problem	NOUN
ijassa-1239	300	18	of	of	ADP
ijassa-1239	300	19	information	information	NOUN
ijassa-1239	300	20	transmission	transmission	NOUN
ijassa-1239	300	21	,	,	PUNCT
ijassa-1239	300	22	56(1	56(1	NUM
ijassa-1239	300	23	)	)	PUNCT
ijassa-1239	300	24	,	,	PUNCT
ijassa-1239	300	25	73–90	73–90	NUM
ijassa-1239	300	26	.	.	PUNCT
ijassa-1239	301	1	9	9	NUM
ijassa-1239	301	2	.	.	X
ijassa-1239	301	3	gorbunova	gorbunova	PROPN
ijassa-1239	301	4	,	,	PUNCT
ijassa-1239	301	5	a.	a.	PROPN
ijassa-1239	301	6	v.	v.	PROPN
ijassa-1239	301	7	&	&	CCONJ
ijassa-1239	301	8	lebedev	lebedev	PROPN
ijassa-1239	301	9	,	,	PUNCT
ijassa-1239	301	10	a.	a.	PROPN
ijassa-1239	301	11	v.	v.	PROPN
ijassa-1239	301	12	(	(	PUNCT
ijassa-1239	301	13	2022	2022	NUM
ijassa-1239	301	14	)	)	PUNCT
ijassa-1239	301	15	.	.	PUNCT
ijassa-1239	302	1	response	response	NOUN
ijassa-1239	302	2	time	time	NOUN
ijassa-1239	302	3	estimate	estimate	NOUN
ijassa-1239	302	4	for	for	ADP
ijassa-1239	302	5	a	a	DET
ijassa-1239	302	6	fork	fork	NOUN
ijassa-1239	302	7	-	-	PUNCT
ijassa-1239	302	8	join	join	NOUN
ijassa-1239	302	9	system	system	NOUN
ijassa-1239	302	10	with	with	ADP
ijassa-1239	302	11	pareto	pareto	ADJ
ijassa-1239	302	12	distributed	distribute	VERB
ijassa-1239	302	13	service	service	NOUN
ijassa-1239	302	14	time	time	NOUN
ijassa-1239	302	15	as	as	ADP
ijassa-1239	302	16	a	a	DET
ijassa-1239	302	17	model	model	NOUN
ijassa-1239	302	18	of	of	ADP
ijassa-1239	302	19	a	a	DET
ijassa-1239	302	20	cloud	cloud	NOUN
ijassa-1239	302	21	computing	compute	VERB
ijassa-1239	302	22	system	system	NOUN
ijassa-1239	302	23	using	use	VERB
ijassa-1239	302	24	neural	neural	ADJ
ijassa-1239	302	25	networks	network	NOUN
ijassa-1239	302	26	,	,	PUNCT
ijassa-1239	302	27	communications	communication	NOUN
ijassa-1239	302	28	in	in	ADP
ijassa-1239	302	29	computer	computer	NOUN
ijassa-1239	302	30	and	and	CCONJ
ijassa-1239	302	31	information	information	NOUN
ijassa-1239	302	32	science	science	NOUN
ijassa-1239	302	33	,	,	PUNCT
ijassa-1239	302	34	1552	1552	NUM
ijassa-1239	302	35	,	,	PUNCT
ijassa-1239	302	36	318–332	318–332	NUM
ijassa-1239	302	37	.	.	PUNCT
ijassa-1239	303	1	10	10	NUM
ijassa-1239	303	2	.	.	X
ijassa-1239	303	3	gorbunova	gorbunova	PROPN
ijassa-1239	303	4	,	,	PUNCT
ijassa-1239	303	5	a.	a.	PROPN
ijassa-1239	303	6	v.	v.	PROPN
ijassa-1239	303	7	&	&	CCONJ
ijassa-1239	303	8	vishnevsky	vishnevsky	PROPN
ijassa-1239	303	9	,	,	PUNCT
ijassa-1239	303	10	v.	v.	ADP
ijassa-1239	303	11	m.	m.	NOUN
ijassa-1239	303	12	(	(	PUNCT
ijassa-1239	303	13	2020	2020	NUM
ijassa-1239	303	14	)	)	PUNCT
ijassa-1239	303	15	.	.	PUNCT
ijassa-1239	304	1	estimating	estimate	VERB
ijassa-1239	304	2	the	the	DET
ijassa-1239	304	3	response	response	NOUN
ijassa-1239	304	4	time	time	NOUN
ijassa-1239	304	5	of	of	ADP
ijassa-1239	304	6	a	a	DET
ijassa-1239	304	7	cloud	cloud	NOUN
ijassa-1239	304	8	computing	compute	VERB
ijassa-1239	304	9	system	system	NOUN
ijassa-1239	304	10	with	with	ADP
ijassa-1239	304	11	the	the	DET
ijassa-1239	304	12	help	help	NOUN
ijassa-1239	304	13	of	of	ADP
ijassa-1239	304	14	neural	neural	ADJ
ijassa-1239	304	15	networks	network	NOUN
ijassa-1239	304	16	,	,	PUNCT
ijassa-1239	304	17	advances	advance	NOUN
ijassa-1239	304	18	in	in	ADP
ijassa-1239	304	19	systems	system	NOUN
ijassa-1239	304	20	science	science	NOUN
ijassa-1239	304	21	and	and	CCONJ
ijassa-1239	304	22	applications	application	NOUN
ijassa-1239	304	23	,	,	PUNCT
ijassa-1239	304	24	20(3	20(3	NOUN
ijassa-1239	304	25	)	)	PUNCT
ijassa-1239	304	26	,	,	PUNCT
ijassa-1239	304	27	105–112	105–112	NUM
ijassa-1239	304	28	.	.	PUNCT
ijassa-1239	305	1	11	11	NUM
ijassa-1239	305	2	.	.	X
ijassa-1239	306	1	khalid	khalid	PROPN
ijassa-1239	306	2	,	,	PUNCT
ijassa-1239	306	3	m.	m.	PROPN
ijassa-1239	306	4	&	&	CCONJ
ijassa-1239	306	5	yousaf	yousaf	PROPN
ijassa-1239	306	6	,	,	PUNCT
ijassa-1239	306	7	m.	m.	NOUN
ijassa-1239	306	8	m.	m.	NOUN
ijassa-1239	306	9	(	(	PUNCT
ijassa-1239	306	10	2021	2021	NUM
ijassa-1239	306	11	)	)	PUNCT
ijassa-1239	306	12	.	.	PUNCT
ijassa-1239	307	1	a	a	DET
ijassa-1239	307	2	comparative	comparative	ADJ
ijassa-1239	307	3	analysis	analysis	NOUN
ijassa-1239	307	4	of	of	ADP
ijassa-1239	307	5	big	big	ADJ
ijassa-1239	307	6	data	datum	NOUN
ijassa-1239	307	7	frameworks	framework	NOUN
ijassa-1239	307	8	:	:	PUNCT
ijassa-1239	307	9	an	an	DET
ijassa-1239	307	10	adoption	adoption	NOUN
ijassa-1239	307	11	perspective	perspective	NOUN
ijassa-1239	307	12	,	,	PUNCT
ijassa-1239	307	13	applied	apply	VERB
ijassa-1239	307	14	sciences	science	NOUN
ijassa-1239	307	15	,	,	PUNCT
ijassa-1239	307	16	11(22	11(22	PROPN
ijassa-1239	307	17	)	)	PUNCT
ijassa-1239	307	18	,	,	PUNCT
ijassa-1239	307	19	11033	11033	NUM
ijassa-1239	307	20	.	.	PUNCT
ijassa-1239	308	1	12	12	NUM
ijassa-1239	308	2	.	.	X
ijassa-1239	308	3	meisner	meisner	PROPN
ijassa-1239	308	4	,	,	PUNCT
ijassa-1239	308	5	d.	d.	PROPN
ijassa-1239	308	6	,	,	PUNCT
ijassa-1239	308	7	junjie	junjie	PROPN
ijassa-1239	308	8	,	,	PUNCT
ijassa-1239	308	9	w.	w.	PROPN
ijassa-1239	308	10	&	&	CCONJ
ijassa-1239	308	11	wenisch	wenisch	PROPN
ijassa-1239	308	12	,	,	PUNCT
ijassa-1239	308	13	t.	t.	PROPN
ijassa-1239	308	14	f.	f.	PROPN
ijassa-1239	308	15	(	(	PUNCT
ijassa-1239	308	16	2012	2012	NUM
ijassa-1239	308	17	)	)	PUNCT
ijassa-1239	308	18	.	.	PUNCT
ijassa-1239	309	1	bighouse	bighouse	NOUN
ijassa-1239	309	2	:	:	PUNCT
ijassa-1239	309	3	a	a	DET
ijassa-1239	309	4	simulation	simulation	NOUN
ijassa-1239	309	5	infrastructure	infrastructure	NOUN
ijassa-1239	309	6	for	for	ADP
ijassa-1239	309	7	data	datum	NOUN
ijassa-1239	309	8	center	center	NOUN
ijassa-1239	309	9	systems	system	NOUN
ijassa-1239	309	10	,	,	PUNCT
ijassa-1239	309	11	in	in	ADP
ijassa-1239	309	12	proc	proc	NOUN
ijassa-1239	309	13	.	.	PUNCT
ijassa-1239	310	1	ieee	ieee	PROPN
ijassa-1239	310	2	international	international	ADJ
ijassa-1239	310	3	symposium	symposium	NOUN
ijassa-1239	310	4	on	on	ADP
ijassa-1239	310	5	performance	performance	NOUN
ijassa-1239	310	6	analysis	analysis	NOUN
ijassa-1239	310	7	of	of	ADP
ijassa-1239	310	8	systems	system	NOUN
ijassa-1239	310	9	&	&	CCONJ
ijassa-1239	310	10	software	software	PROPN
ijassa-1239	310	11	,	,	PUNCT
ijassa-1239	310	12	new	new	PROPN
ijassa-1239	310	13	brunswick	brunswick	PROPN
ijassa-1239	310	14	,	,	PUNCT
ijassa-1239	310	15	nj	nj	PROPN
ijassa-1239	310	16	,	,	PUNCT
ijassa-1239	310	17	usa	usa	PROPN
ijassa-1239	310	18	,	,	PUNCT
ijassa-1239	310	19	35–45	35–45	NUM
ijassa-1239	310	20	.	.	NOUN
ijassa-1239	310	21	13	13	NUM
ijassa-1239	310	22	.	.	X
ijassa-1239	310	23	meisner	meisner	PROPN
ijassa-1239	310	24	,	,	PUNCT
ijassa-1239	310	25	d.	d.	PROPN
ijassa-1239	310	26	,	,	PUNCT
ijassa-1239	310	27	sadler	sadler	NOUN
ijassa-1239	310	28	,	,	PUNCT
ijassa-1239	310	29	c.	c.	PROPN
ijassa-1239	310	30	m.	m.	PROPN
ijassa-1239	310	31	,	,	PUNCT
ijassa-1239	310	32	barroso	barroso	PROPN
ijassa-1239	310	33	,	,	PUNCT
ijassa-1239	310	34	a.	a.	PROPN
ijassa-1239	310	35	l.	l.	PROPN
ijassa-1239	310	36	,	,	PUNCT
ijassa-1239	310	37	weber	weber	PROPN
ijassa-1239	310	38	,	,	PUNCT
ijassa-1239	310	39	w.	w.	PROPN
ijassa-1239	310	40	d.	d.	PROPN
ijassa-1239	310	41	&	&	CCONJ
ijassa-1239	310	42	wenisch	wenisch	PROPN
ijassa-1239	310	43	,	,	PUNCT
ijassa-1239	310	44	t.	t.	PROPN
ijassa-1239	310	45	f.	f.	PROPN
ijassa-1239	310	46	(	(	PUNCT
ijassa-1239	310	47	2011	2011	NUM
ijassa-1239	310	48	)	)	PUNCT
ijassa-1239	310	49	.	.	PUNCT
ijassa-1239	311	1	power	power	NOUN
ijassa-1239	311	2	management	management	NOUN
ijassa-1239	311	3	of	of	ADP
ijassa-1239	311	4	online	online	ADJ
ijassa-1239	311	5	data	datum	NOUN
ijassa-1239	311	6	-	-	PUNCT
ijassa-1239	311	7	intensive	intensive	ADJ
ijassa-1239	311	8	services	service	NOUN
ijassa-1239	311	9	,	,	PUNCT
ijassa-1239	311	10	acm	acm	PROPN
ijassa-1239	311	11	sigarch	sigarch	NOUN
ijassa-1239	311	12	computer	computer	NOUN
ijassa-1239	311	13	architecture	architecture	NOUN
ijassa-1239	311	14	news	news	NOUN
ijassa-1239	311	15	,	,	PUNCT
ijassa-1239	311	16	39(2	39(2	NUM
ijassa-1239	311	17	)	)	PUNCT
ijassa-1239	311	18	,	,	PUNCT
ijassa-1239	311	19	319–330	319–330	NUM
ijassa-1239	311	20	.	.	NOUN
ijassa-1239	311	21	14	14	NUM
ijassa-1239	311	22	.	.	PUNCT
ijassa-1239	312	1	nelson	nelson	PROPN
ijassa-1239	312	2	,	,	PUNCT
ijassa-1239	312	3	r.	r.	PROPN
ijassa-1239	312	4	&	&	CCONJ
ijassa-1239	312	5	tantawi	tantawi	PROPN
ijassa-1239	312	6	,	,	PUNCT
ijassa-1239	312	7	a.	a.	PROPN
ijassa-1239	312	8	n.	n.	PROPN
ijassa-1239	312	9	(	(	PUNCT
ijassa-1239	312	10	1988	1988	NUM
ijassa-1239	312	11	)	)	PUNCT
ijassa-1239	312	12	.	.	PUNCT
ijassa-1239	313	1	approximate	approximate	ADJ
ijassa-1239	313	2	analysis	analysis	NOUN
ijassa-1239	313	3	of	of	ADP
ijassa-1239	313	4	fork	fork	NOUN
ijassa-1239	313	5	/	/	SYM
ijassa-1239	313	6	join	join	NOUN
ijassa-1239	313	7	synchronization	synchronization	NOUN
ijassa-1239	313	8	in	in	ADP
ijassa-1239	313	9	parallel	parallel	ADJ
ijassa-1239	313	10	queues	queue	NOUN
ijassa-1239	313	11	,	,	PUNCT
ijassa-1239	313	12	ieee	ieee	NOUN
ijassa-1239	313	13	transactions	transaction	NOUN
ijassa-1239	313	14	on	on	ADP
ijassa-1239	313	15	computers	computer	NOUN
ijassa-1239	313	16	,	,	PUNCT
ijassa-1239	313	17	37	37	NUM
ijassa-1239	313	18	,	,	PUNCT
ijassa-1239	313	19	739–743	739–743	NUM
ijassa-1239	313	20	.	.	PUNCT
ijassa-1239	314	1	15	15	NUM
ijassa-1239	314	2	.	.	PUNCT
ijassa-1239	315	1	nguyen	nguyen	NOUN
ijassa-1239	315	2	,	,	PUNCT
ijassa-1239	315	3	m.	m.	NOUN
ijassa-1239	315	4	,	,	PUNCT
ijassa-1239	315	5	alesawi	alesawi	PROPN
ijassa-1239	315	6	,	,	PUNCT
ijassa-1239	315	7	s.	s.	PROPN
ijassa-1239	315	8	,	,	PUNCT
ijassa-1239	315	9	li	li	PROPN
ijassa-1239	315	10	,	,	PUNCT
ijassa-1239	315	11	n.	n.	NOUN
ijassa-1239	315	12	,	,	PUNCT
ijassa-1239	315	13	che	che	PROPN
ijassa-1239	315	14	,	,	PUNCT
ijassa-1239	315	15	h.	h.	PROPN
ijassa-1239	315	16	&	&	CCONJ
ijassa-1239	315	17	jiang	jiang	PROPN
ijassa-1239	315	18	,	,	PUNCT
ijassa-1239	315	19	h.	h.	PROPN
ijassa-1239	315	20	(	(	PUNCT
ijassa-1239	315	21	2020	2020	NUM
ijassa-1239	315	22	)	)	PUNCT
ijassa-1239	315	23	.	.	PUNCT
ijassa-1239	316	1	a	a	DET
ijassa-1239	316	2	black	black	ADJ
ijassa-1239	316	3	-	-	PUNCT
ijassa-1239	316	4	box	box	NOUN
ijassa-1239	316	5	fork	fork	NOUN
ijassa-1239	316	6	-	-	PUNCT
ijassa-1239	316	7	join	join	NOUN
ijassa-1239	316	8	latency	latency	NOUN
ijassa-1239	316	9	prediction	prediction	NOUN
ijassa-1239	316	10	model	model	NOUN
ijassa-1239	316	11	for	for	ADP
ijassa-1239	316	12	data	data	NOUN
ijassa-1239	316	13	-	-	PUNCT
ijassa-1239	316	14	intensive	intensive	ADJ
ijassa-1239	316	15	applications	application	NOUN
ijassa-1239	316	16	,	,	PUNCT
ijassa-1239	316	17	ieee	ieee	NOUN
ijassa-1239	316	18	transactions	transaction	NOUN
ijassa-1239	316	19	on	on	ADP
ijassa-1239	316	20	parallel	parallel	ADJ
ijassa-1239	316	21	and	and	CCONJ
ijassa-1239	316	22	distributed	distributed	ADJ
ijassa-1239	316	23	systems	system	NOUN
ijassa-1239	316	24	,	,	PUNCT
ijassa-1239	316	25	31(9	31(9	NUM
ijassa-1239	316	26	)	)	PUNCT
ijassa-1239	316	27	,	,	PUNCT
ijassa-1239	316	28	1983–2000	1983–2000	NUM
ijassa-1239	316	29	.	.	PUNCT
ijassa-1239	317	1	16	16	NUM
ijassa-1239	317	2	.	.	PUNCT
ijassa-1239	318	1	nguyen	nguyen	NOUN
ijassa-1239	318	2	,	,	PUNCT
ijassa-1239	318	3	m.	m.	NOUN
ijassa-1239	318	4	,	,	PUNCT
ijassa-1239	318	5	alesawi	alesawi	PROPN
ijassa-1239	318	6	,	,	PUNCT
ijassa-1239	318	7	s.	s.	PROPN
ijassa-1239	318	8	,	,	PUNCT
ijassa-1239	318	9	li	li	PROPN
ijassa-1239	318	10	,	,	PUNCT
ijassa-1239	318	11	n.	n.	NOUN
ijassa-1239	318	12	,	,	PUNCT
ijassa-1239	318	13	che	che	PROPN
ijassa-1239	318	14	,	,	PUNCT
ijassa-1239	318	15	h.	h.	PROPN
ijassa-1239	318	16	&	&	CCONJ
ijassa-1239	318	17	jiang	jiang	PROPN
ijassa-1239	318	18	,	,	PUNCT
ijassa-1239	318	19	h.	h.	PROPN
ijassa-1239	318	20	(	(	PUNCT
ijassa-1239	318	21	2018	2018	NUM
ijassa-1239	318	22	)	)	PUNCT
ijassa-1239	318	23	.	.	PUNCT
ijassa-1239	319	1	forktail	forktail	NOUN
ijassa-1239	319	2	:	:	PUNCT
ijassa-1239	319	3	a	a	DET
ijassa-1239	319	4	black	black	ADJ
ijassa-1239	319	5	-	-	PUNCT
ijassa-1239	319	6	box	box	NOUN
ijassa-1239	319	7	fork	fork	NOUN
ijassa-1239	319	8	-	-	PUNCT
ijassa-1239	319	9	join	join	NOUN
ijassa-1239	319	10	tail	tail	NOUN
ijassa-1239	319	11	latency	latency	NOUN
ijassa-1239	319	12	prediction	prediction	NOUN
ijassa-1239	319	13	model	model	NOUN
ijassa-1239	319	14	for	for	ADP
ijassa-1239	319	15	user	user	NOUN
ijassa-1239	319	16	-	-	PUNCT
ijassa-1239	319	17	facing	face	VERB
ijassa-1239	319	18	datacenter	datacenter	NOUN
ijassa-1239	319	19	workloads	workload	NOUN
ijassa-1239	319	20	,	,	PUNCT
ijassa-1239	319	21	in	in	ADP
ijassa-1239	319	22	proc	proc	NOUN
ijassa-1239	319	23	.	.	PUNCT
ijassa-1239	320	1	27th	27th	ADJ
ijassa-1239	320	2	int	int	NOUN
ijassa-1239	320	3	.	.	PUNCT
ijassa-1239	321	1	symp	symp	PROPN
ijassa-1239	321	2	.	.	PUNCT
ijassa-1239	322	1	high	high	ADJ
ijassa-1239	322	2	-	-	PUNCT
ijassa-1239	322	3	perform	perform	NOUN
ijassa-1239	322	4	.	.	PUNCT
ijassa-1239	323	1	parallel	parallel	ADJ
ijassa-1239	323	2	distrib	distrib	NOUN
ijassa-1239	323	3	.	.	PUNCT
ijassa-1239	324	1	comput	comput	PROPN
ijassa-1239	324	2	.	.	PUNCT
ijassa-1239	324	3	,	,	PUNCT
ijassa-1239	324	4	206–217	206–217	NUM
ijassa-1239	324	5	.	.	PUNCT
ijassa-1239	325	1	17	17	NUM
ijassa-1239	325	2	.	.	X
ijassa-1239	325	3	de	de	PROPN
ijassa-1239	325	4	oliveira	oliveira	PROPN
ijassa-1239	325	5	,	,	PUNCT
ijassa-1239	325	6	d.	d.	PROPN
ijassa-1239	325	7	c.	c.	PROPN
ijassa-1239	325	8	,	,	PUNCT
ijassa-1239	325	9	liu	liu	PROPN
ijassa-1239	325	10	,	,	PUNCT
ijassa-1239	325	11	j.	j.	PROPN
ijassa-1239	325	12	&	&	CCONJ
ijassa-1239	325	13	pacitti	pacitti	PROPN
ijassa-1239	325	14	,	,	PUNCT
ijassa-1239	325	15	e.	e.	PROPN
ijassa-1239	325	16	(	(	PUNCT
ijassa-1239	325	17	2019	2019	NUM
ijassa-1239	325	18	)	)	PUNCT
ijassa-1239	325	19	.	.	PUNCT
ijassa-1239	326	1	data	datum	NOUN
ijassa-1239	326	2	-	-	PUNCT
ijassa-1239	326	3	intensive	intensive	ADJ
ijassa-1239	326	4	workflow	workflow	NOUN
ijassa-1239	326	5	management	management	NOUN
ijassa-1239	326	6	:	:	PUNCT
ijassa-1239	326	7	for	for	ADP
ijassa-1239	326	8	clouds	cloud	NOUN
ijassa-1239	326	9	and	and	CCONJ
ijassa-1239	326	10	data	datum	NOUN
ijassa-1239	326	11	-	-	PUNCT
ijassa-1239	326	12	intensive	intensive	ADJ
ijassa-1239	326	13	and	and	CCONJ
ijassa-1239	326	14	scalable	scalable	ADJ
ijassa-1239	326	15	computing	compute	VERB
ijassa-1239	326	16	environments	environment	NOUN
ijassa-1239	326	17	.	.	PUNCT
ijassa-1239	327	1	synthesis	synthesis	NOUN
ijassa-1239	327	2	lectures	lecture	NOUN
ijassa-1239	327	3	on	on	ADP
ijassa-1239	327	4	data	datum	NOUN
ijassa-1239	327	5	management	management	NOUN
ijassa-1239	327	6	,	,	PUNCT
ijassa-1239	327	7	14	14	NUM
ijassa-1239	327	8	,	,	PUNCT
ijassa-1239	327	9	1–179	1–179	NUM
ijassa-1239	327	10	.	.	PUNCT
ijassa-1239	328	1	18	18	NUM
ijassa-1239	328	2	.	.	X
ijassa-1239	329	1	qiu	qiu	PROPN
ijassa-1239	329	2	,	,	PUNCT
ijassa-1239	329	3	z.	z.	PROPN
ijassa-1239	329	4	,	,	PUNCT
ijassa-1239	329	5	prez	prez	PROPN
ijassa-1239	329	6	,	,	PUNCT
ijassa-1239	329	7	j.	j.	PROPN
ijassa-1239	329	8	f.	f.	PROPN
ijassa-1239	329	9	&	&	CCONJ
ijassa-1239	329	10	harrison	harrison	PROPN
ijassa-1239	329	11	,	,	PUNCT
ijassa-1239	329	12	p.	p.	NOUN
ijassa-1239	329	13	(	(	PUNCT
ijassa-1239	329	14	2015	2015	NUM
ijassa-1239	329	15	)	)	PUNCT
ijassa-1239	329	16	.	.	PUNCT
ijassa-1239	330	1	beyond	beyond	ADP
ijassa-1239	330	2	the	the	DET
ijassa-1239	330	3	mean	mean	NOUN
ijassa-1239	330	4	in	in	ADP
ijassa-1239	330	5	fork	fork	NOUN
ijassa-1239	330	6	-	-	PUNCT
ijassa-1239	330	7	join	join	NOUN
ijassa-1239	330	8	queues	queue	NOUN
ijassa-1239	330	9	:	:	PUNCT
ijassa-1239	330	10	efficient	efficient	ADJ
ijassa-1239	330	11	approximation	approximation	NOUN
ijassa-1239	330	12	for	for	ADP
ijassa-1239	330	13	response	response	NOUN
ijassa-1239	330	14	-	-	PUNCT
ijassa-1239	330	15	time	time	NOUN
ijassa-1239	330	16	tails	tail	NOUN
ijassa-1239	330	17	,	,	PUNCT
ijassa-1239	330	18	performance	performance	NOUN
ijassa-1239	330	19	evaluation	evaluation	NOUN
ijassa-1239	330	20	,	,	PUNCT
ijassa-1239	330	21	91	91	NUM
ijassa-1239	330	22	,	,	PUNCT
ijassa-1239	330	23	99–116	99–116	PROPN
ijassa-1239	330	24	.	.	PUNCT
ijassa-1239	330	25	19	19	NUM
ijassa-1239	330	26	.	.	X
ijassa-1239	330	27	reinsel	reinsel	PROPN
ijassa-1239	330	28	,	,	PUNCT
ijassa-1239	330	29	d.	d.	PROPN
ijassa-1239	330	30	,	,	PUNCT
ijassa-1239	330	31	gantz	gantz	PROPN
ijassa-1239	330	32	,	,	PUNCT
ijassa-1239	330	33	j.	j.	PROPN
ijassa-1239	330	34	&	&	CCONJ
ijassa-1239	330	35	rydning	rydning	PROPN
ijassa-1239	330	36	,	,	PUNCT
ijassa-1239	330	37	j.	j.	PROPN
ijassa-1239	330	38	(	(	PUNCT
ijassa-1239	330	39	2018	2018	NUM
ijassa-1239	330	40	)	)	PUNCT
ijassa-1239	330	41	.	.	PUNCT
ijassa-1239	331	1	idc	idc	PROPN
ijassa-1239	331	2	report	report	PROPN
ijassa-1239	331	3	:	:	PUNCT
ijassa-1239	331	4	the	the	DET
ijassa-1239	331	5	digitization	digitization	NOUN
ijassa-1239	331	6	of	of	ADP
ijassa-1239	331	7	the	the	DET
ijassa-1239	331	8	world	world	NOUN
ijassa-1239	331	9	from	from	ADP
ijassa-1239	331	10	edge	edge	NOUN
ijassa-1239	331	11	to	to	ADP
ijassa-1239	331	12	core	core	NOUN
ijassa-1239	331	13	.	.	PUNCT
ijassa-1239	332	1	idc	idc	PROPN
ijassa-1239	332	2	white	white	PROPN
ijassa-1239	332	3	paper	paper	PROPN
ijassa-1239	332	4	no.us44413318	no.us44413318	PROPN
ijassa-1239	332	5	.	.	PUNCT
ijassa-1239	333	1	framingham	framingham	PROPN
ijassa-1239	333	2	,	,	PUNCT
ijassa-1239	333	3	ma	ma	PROPN
ijassa-1239	333	4	:	:	PUNCT
ijassa-1239	333	5	international	international	ADJ
ijassa-1239	333	6	data	datum	NOUN
ijassa-1239	333	7	corporation	corporation	NOUN
ijassa-1239	333	8	.	.	PUNCT
ijassa-1239	334	1	20	20	NUM
ijassa-1239	334	2	.	.	X
ijassa-1239	335	1	thomasian	thomasian	ADJ
ijassa-1239	335	2	,	,	PUNCT
ijassa-1239	335	3	a.	a.	NOUN
ijassa-1239	335	4	(	(	PUNCT
ijassa-1239	335	5	2014	2014	NUM
ijassa-1239	335	6	)	)	PUNCT
ijassa-1239	335	7	.	.	PUNCT
ijassa-1239	336	1	analysis	analysis	NOUN
ijassa-1239	336	2	of	of	ADP
ijassa-1239	336	3	fork	fork	NOUN
ijassa-1239	336	4	/	/	SYM
ijassa-1239	336	5	join	join	NOUN
ijassa-1239	336	6	and	and	CCONJ
ijassa-1239	336	7	related	related	ADJ
ijassa-1239	336	8	queueing	queueing	NOUN
ijassa-1239	336	9	systems	system	NOUN
ijassa-1239	336	10	,	,	PUNCT
ijassa-1239	336	11	acm	acm	PROPN
ijassa-1239	336	12	computing	computing	NOUN
ijassa-1239	336	13	surveys	survey	NOUN
ijassa-1239	336	14	(	(	PUNCT
ijassa-1239	336	15	csur	csur	NOUN
ijassa-1239	336	16	)	)	PUNCT
ijassa-1239	336	17	,	,	PUNCT
ijassa-1239	336	18	47(2	47(2	PROPN
ijassa-1239	336	19	)	)	PUNCT
ijassa-1239	336	20	,	,	PUNCT
ijassa-1239	336	21	17:1–17:71	17:1–17:71	NUM
ijassa-1239	336	22	.	.	PUNCT
ijassa-1239	337	1	copyright	copyright	NOUN
ijassa-1239	337	2	©	©	PROPN
ijassa-1239	337	3	2022	2022	NUM
ijassa-1239	337	4	assa	assa	NOUN
ijassa-1239	337	5	.	.	PUNCT
ijassa-1239	338	1	adv	adv	PROPN
ijassa-1239	338	2	syst	syst	PROPN
ijassa-1239	338	3	sci	sci	PROPN
ijassa-1239	338	4	appl	appl	PROPN
ijassa-1239	338	5	(	(	PUNCT
ijassa-1239	338	6	2022	2022	NUM
ijassa-1239	338	7	)	)	PUNCT
ijassa-1239	338	8	the	the	DET
ijassa-1239	338	9	analysis	analysis	NOUN
ijassa-1239	338	10	of	of	ADP
ijassa-1239	338	11	big	big	ADJ
ijassa-1239	338	12	data	datum	NOUN
ijassa-1239	338	13	centers	center	NOUN
ijassa-1239	338	14	performance	performance	NOUN
ijassa-1239	338	15	83	83	NUM
ijassa-1239	338	16	21	21	NUM
ijassa-1239	338	17	.	.	PUNCT
ijassa-1239	339	1	vishnevsky	vishnevsky	ADJ
ijassa-1239	339	2	,	,	PUNCT
ijassa-1239	339	3	v.	v.	ADP
ijassa-1239	339	4	m.	m.	PROPN
ijassa-1239	339	5	&	&	CCONJ
ijassa-1239	339	6	gorbunova	gorbunova	PROPN
ijassa-1239	339	7	,	,	PUNCT
ijassa-1239	339	8	a.	a.	PROPN
ijassa-1239	339	9	v.	v.	PROPN
ijassa-1239	339	10	(	(	PUNCT
ijassa-1239	339	11	2022	2022	NUM
ijassa-1239	339	12	)	)	PUNCT
ijassa-1239	339	13	.	.	PUNCT
ijassa-1239	340	1	application	application	NOUN
ijassa-1239	340	2	of	of	ADP
ijassa-1239	340	3	machine	machine	NOUN
ijassa-1239	340	4	learning	learn	VERB
ijassa-1239	340	5	methods	method	NOUN
ijassa-1239	340	6	to	to	ADP
ijassa-1239	340	7	solving	solve	VERB
ijassa-1239	340	8	problems	problem	NOUN
ijassa-1239	340	9	of	of	ADP
ijassa-1239	340	10	queuing	queue	VERB
ijassa-1239	340	11	theory	theory	NOUN
ijassa-1239	340	12	,	,	PUNCT
ijassa-1239	340	13	communications	communication	NOUN
ijassa-1239	340	14	in	in	ADP
ijassa-1239	340	15	computer	computer	NOUN
ijassa-1239	340	16	and	and	CCONJ
ijassa-1239	340	17	information	information	NOUN
ijassa-1239	340	18	science	science	NOUN
ijassa-1239	340	19	,	,	PUNCT
ijassa-1239	340	20	in	in	ADP
ijassa-1239	340	21	print	print	NOUN
ijassa-1239	340	22	.	.	PUNCT
ijassa-1239	341	1	22	22	NUM
ijassa-1239	341	2	.	.	PUNCT
ijassa-1239	342	1	wang	wang	PROPN
ijassa-1239	342	2	,	,	PUNCT
ijassa-1239	342	3	w.	w.	PROPN
ijassa-1239	342	4	,	,	PUNCT
ijassa-1239	342	5	harchol	harchol	NOUN
ijassa-1239	342	6	-	-	PUNCT
ijassa-1239	342	7	balter	balter	NOUN
ijassa-1239	342	8	,	,	PUNCT
ijassa-1239	342	9	m.	m.	NOUN
ijassa-1239	342	10	,	,	PUNCT
ijassa-1239	342	11	jiang	jiang	PROPN
ijassa-1239	342	12	,	,	PUNCT
ijassa-1239	342	13	h.	h.	PROPN
ijassa-1239	342	14	,	,	PUNCT
ijassa-1239	342	15	scheller	scheller	NOUN
ijassa-1239	342	16	-	-	PUNCT
ijassa-1239	342	17	wolf	wolf	PROPN
ijassa-1239	342	18	,	,	PUNCT
ijassa-1239	342	19	a.	a.	PROPN
ijassa-1239	342	20	&	&	CCONJ
ijassa-1239	342	21	srikant	srikant	PROPN
ijassa-1239	342	22	,	,	PUNCT
ijassa-1239	342	23	r.	r.	PROPN
ijassa-1239	342	24	(	(	PUNCT
ijassa-1239	342	25	2019	2019	NUM
ijassa-1239	342	26	)	)	PUNCT
ijassa-1239	342	27	.	.	PUNCT
ijassa-1239	343	1	delay	delay	NOUN
ijassa-1239	343	2	asymptotics	asymptotic	NOUN
ijassa-1239	343	3	and	and	CCONJ
ijassa-1239	343	4	bounds	bound	NOUN
ijassa-1239	343	5	for	for	ADP
ijassa-1239	343	6	multitask	multitask	ADJ
ijassa-1239	343	7	parallel	parallel	ADJ
ijassa-1239	343	8	jobs	job	NOUN
ijassa-1239	343	9	,	,	PUNCT
ijassa-1239	343	10	queueing	queue	VERB
ijassa-1239	343	11	systems	system	NOUN
ijassa-1239	343	12	,	,	PUNCT
ijassa-1239	343	13	91	91	NUM
ijassa-1239	343	14	,	,	PUNCT
ijassa-1239	343	15	207–239	207–239	NUM
ijassa-1239	343	16	.	.	PUNCT
ijassa-1239	344	1	copyright	copyright	NOUN
ijassa-1239	344	2	©	©	PROPN
ijassa-1239	344	3	2022	2022	NUM
ijassa-1239	344	4	assa	assa	NOUN
ijassa-1239	344	5	.	.	PUNCT
ijassa-1239	345	1	adv	adv	PROPN
ijassa-1239	345	2	syst	syst	PROPN
ijassa-1239	345	3	sci	sci	PROPN
ijassa-1239	345	4	appl	appl	PROPN
ijassa-1239	345	5	(	(	PUNCT
ijassa-1239	345	6	2022	2022	NUM
ijassa-1239	345	7	)	)	PUNCT
ijassa-1239	345	8	introduction	introduction	NOUN
ijassa-1239	345	9	related	relate	VERB
ijassa-1239	345	10	work	work	NOUN
ijassa-1239	345	11	analysis	analysis	NOUN
ijassa-1239	345	12	method	method	NOUN
ijassa-1239	345	13	of	of	ADP
ijassa-1239	345	14	fork	fork	NOUN
ijassa-1239	345	15	-	-	PUNCT
ijassa-1239	345	16	join	join	NOUN
ijassa-1239	345	17	qs	qs	NOUN
ijassa-1239	345	18	using	use	VERB
ijassa-1239	345	19	neural	neural	ADJ
ijassa-1239	345	20	networks	network	NOUN
ijassa-1239	345	21	mathematical	mathematical	ADJ
ijassa-1239	345	22	model	model	NOUN
ijassa-1239	345	23	of	of	ADP
ijassa-1239	345	24	the	the	DET
ijassa-1239	345	25	parallel	parallel	ADJ
ijassa-1239	345	26	structure	structure	NOUN
ijassa-1239	345	27	of	of	ADP
ijassa-1239	345	28	the	the	DET
ijassa-1239	345	29	big	big	ADJ
ijassa-1239	345	30	data	datum	NOUN
ijassa-1239	345	31	processing	processing	NOUN
ijassa-1239	345	32	center	center	NOUN
ijassa-1239	345	33	numerical	numerical	ADJ
ijassa-1239	345	34	experiment	experiment	NOUN
ijassa-1239	345	35	discussion	discussion	NOUN
ijassa-1239	345	36	conclusion	conclusion	NOUN