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CTMJ | traditionalmedicinejournals.com                                    Chinese Traditional Medicine Journal | 2021 | Vol4 |Issue3 

 
 

 

 Chinese Traditional Medical Journal 

Performance Evaluation of Prophet Routing Protocol on 

Different Buffer Management Policies 

Jinh Taeji Hong, Hee Seobh Leeli, 

College of Pharmacology, Chungbuk National University, Chungju 

College of Human Ecology, Pusan National University, Busan College of Pharmacy and Medical 

Research Center, Chungbuk National University, Chungju 

 

 

 

 

 

 

 

 

 

 

 

 

1. Introduction 

Delay Tolerant Networks (DTNs) is the 

one of the most challengeable network 

over the last decade. To overcome 

challenges of the network a possible 

solution is delineate in which internet 

architecture support the intermittent 

networks. In this network no end-to-end 

route is exist between source and 

destination node. Moreover, the 

communication links among nodes in the 

network are irregular, data flows in 

asymmetric way and high latency delay. In 

such type of networks, routing messages is 

a challengeable task because the message 

carrier nodes having limited advance 

Abstract 
Delay Tolerant Networks (DTNs) is the advanced class of Ad-hoc network. 

DTN is wireless network in which connections between nodes are 

occasionally, due to which there is no permanent path is established 

between source and destination node. The connection between nodes are 

made instantly, when one node come into the range of another node. 

Therefore, in these network, message delivery is totally depends open the 

connection of nodes made in network. In DTN, mechanism used for 

routing the message is Store-Carry and Forward (SCF) approach. Each 

node in network has limited buffer space to store message. The message is 

discards or dropped from the buffer space when it is full. To discover 

which message is discards form the buffer space a number of buffer 

management strategies are developed by the researcher such as the first in 

first out (FIFO), Drop oldest, Drop large, Drop last, Drop Random (DR), 

Drop Least Recently Received (DLR), Evict most forward first (MOFO) 

and E-drop drop strategies etc. In this paper performance of Drop Random, 

DLR, MOFO and E-Drop buffer policies are evaluated on Prophet routing 

protocol. 

 

Keywords: DTN, Drop Random, DLR, MOFO and E-Drop. 
 



 

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CTMJ | traditionalmedicinejournals.com                                    Chinese Traditional Medicine Journal | 2021 | Vol4 |Issue3 

 
 

information [1]. To send a message in such 

a network, routing algorithms use store-

carry and forwarding approach (SCF). 

Nodes in DTN have limited resources such 

as bandwidth, buffer space and energy etc. 

So it is necessary to use these limited 

resources in efficient way during routing 

messages from source to destination node. 

To improve the delivery probability of 

message in such a network, the researcher 

proposed different DTN routing such as 

Direct Delivery, First Contact, Epidemic 

[2], Spray and Wait [3], Prophet [4] and 

MaxProp [5]. In this paper, Prophet 

routing protocol is evaluated on different 

buffer management policies. 

 

2. Existing Buffer Management 

Strategies 

The various buffer management 

optimization policies have explored by the 

researchers in the field of Delay Tolerant 

Networks (DTNs) such as FIFO, Drop 

Random, Drop oldest, DLR, Drop Largest, 

MOFO, Drop Last and E-Drop [7,8]. 

These policies are used to decide which 

message is dropped from the buffer space 

if Buffer space is full when a new message 

is arrived from the other nodes 

encountered in the network. In this paper, 

Drop Random, DLR, MOFO and E- Drop 

[11,12, 13] polices are evaluated on 

Prophet routing protocol. 

• Drop Random: In this drop policy 

the messages will be dropped randomly 

from the buffer space to accommodate the 

message transmitting from the other nodes. 

This policy continues to drop the messages 

randomly until it free the buffer space 

required for the newly arrived message 

buffer space. 

• Drop Least Recently Received 

(DLR): In this policy those message will 

be dropped which are stay for long time in 

the buffer space. The main reason behind 

DLR policy is that the messages which are 

stay for long time in a buffer space have a 

lesser amount of delivery probability to be 

conceded to other nodes. 

• Evict most forward first (MOFO): 

In this policy only that messages are 

dropped first from the buffer space which 

are forwarded to utmost number of times, 

i.e. the message which are propagated 

number of hop counts in the network are 

dropped first. In this policy only those 

messages which are travelled less number 

of hop counts are allowed to forward in the 

network. 

• E-Drop: In this policy only those 

messages are dropped from the buffer 

space whose message size is equal or 

greater than the incoming message size 

form encounter node in the network 

otherwise no messages will be dropped 

from the buffer space [6]. 

 

3. Prophet Routing Protocol 

In Prophet routing protocol [9] delivery 

predictability is defined as estimate 

probabilistic metric i.e. P(node a, node b), 

at each node a for each destination node b. 

whenever two nodes meet in the network 

scenario its swap the summary vector 

which consist of delivery predictability 

values. After swap process each nodes 

updates their own delivery predictability in 

the summary vector. A low predictability 

value is assigned to the node if the contacts 

between two nodes are very rare or no 

contact exists between two nodes. If the 

nodes are meet regular interval then it 

delivery predictability is very high. The 



 

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CTMJ | traditionalmedicinejournals.com                                    Chinese Traditional Medicine Journal | 2021 | Vol4 |Issue3 

 
 

transitivity property of Prophet routing 

protocol state that if node A regularly 

meets B and node B regularly meet node 

C, then C is appropriate node for A, hence 

A marks C delivery predictability value as 

high in the summary vector. The operation 

performed by the Prophet routing protocol 

is totally depend upon the delivery 

predictability value in the summary vector. 

The calculation of delivery predictability 

of nodes is divided into three parts. 

Direct update: Direct update is done 

whenever the two nodes a and b are 

encounter directly with each other. The 

equation 1. given below show the direct 

update of delivery predictability values. 

(𝑎,𝑏)   = 𝑃o𝑙 ) + (1 − 𝑃o𝑙𝑑   ) 𝑃i𝑛i𝑡   

…….(1) 

  

Where 

𝑃o𝑙𝑑   = Value of P(a, b) before updating 

𝑃i𝑛i𝑡 ∈ [0,1] = initialization constant. 

  

(𝑎,𝑏 

 (𝑎,𝑏) 

 Aging : In case of aging, the equation 2 

given below decreases the node delivery 

predictability by the time elapsed without 

direct contact between two nodes a and b. 

(𝑎,𝑏)   =  o𝑙𝑑  ᵞ𝐾 (2) 

Where 

ᵞ ∈ [0, 1] = aging constant. 

K= number of time units that have elapsed 

since the last time the metric was aged. 

Transitive update: 

In case of transitivity update, the equation 

3 given below update the delivery 

predictability of node a towards node b 

during the transitive contact among node a 

and node c. 

(𝑎,𝑏) = 𝑃o𝑙 ) + (1 − 𝑃o𝑙𝑑   ) 𝑃(𝑎,𝑐) 𝑃(𝑐,𝑏) 

𝛽 …..(3) 

 Where 

 (𝑎,𝑏 

 (𝑎,𝑏) 

  

β ∈ [0, 1] = transitivity constant which 

reflects the impact of transitivity on the 

delivery predictability. 

4. Performance Metrics 

The performances of various buffer drop 

strategies are evaluated by using Epidemic 

routing protocol. The following metrics are 

used to evaluate the performance [10]: 

• Message Delivery Probability 

(MDP): It is defined as the ratio of the 

number of messages actually delivered to 

the destination and the number of 

messages sent by the sender. 

• MDP = no of message delivered to 

destination/ no of message sent by sender 

• Number of Message Drop 

(NMD): Number of Message drop is the 

ratio of message drop during transmission 

to destinations among all messages 

generated. 

• Overhead Ratio (OHR): It is 

defined as the ratio of total number of 

relayed messages by source nodes minus 

total number of delivered messages to the 

destination nodes divided by total number 

of delivered messages to the destination 

nodes. 

• Average Delivery Latency 

(ADL):The average time taken to deliver 

the message form source nodes to 

destination nodes is called average 

delivery latency. 

ADL=Average         (total         time         

taken         to          deliver          the          

message form source nodes to destination 

nodes) 



 

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CTMJ | traditionalmedicinejournals.com                                    Chinese Traditional Medicine Journal | 2021 | Vol4 |Issue3 

 
 

5. Simulation and Results 

In DTN, different types of network 

environments can be designed and 

implemented, in current network setting 

two types of groups are considered, first 

group is pedestrians which engaged 50 

nodes, second is cars which occupied 50 

nodes. The Shortest Path Map Based 

Movement Model mobility model is used 

in our evaluation. The simulation area is 

4500m x 3400m. 

Table 1. Parameter Setting 

Parameter 
Pedestrians 

(P) 
Cars 

(C) 

No. of hosts 50 50 

Speed 0.5-1.5 

km/h 

2.7- 13.9 

km/h 

Router Prophet 

Buffer Capacity 2-10MB 

Message size 200, 500 KB 

Message Inter- 

arrival Time 
25-35 seconds 

Transmission 

speed 
5Mbps 

World Size 

(meters) 
4500 x 3400m 

Simulation 
Time 

72,000 
sec 

 Message Delivery Probability 

(MDP) 

From fig.1 the following points are 

evaluated: 

• In Prophet routing protocol the 

delivery probability of the entire drop 

policies is increases with increasing the 

buffer size because Prophet routing 

protocol provides the information towards 

destination node by tracing the meeting 

between nodes and assigning weight to 

these meeting whether they meet directly 

or by intermediate nodes. 

• In Prophet routing protocol, E-drop 

policy has the highest delivery probability 

among all the drop policies. Its delivery 

probability is 50% throughout the 

scenario. Its maximum delivery probability 

is 67.51% at buffer size 10MB. 
 

 

 

 

 

  

 

 

 

 

 

Number of Message Dropped (NMD) 

From figure 3 the following points are 

concluded: 

• In Prophet routing protocol, as the buffer size increases nodes have enough capacity to accommodate the messages therefore number of message dropped ratio will be decrease and delivery ratio will increase as shown in fig. 1 

• In Prophet routing protocol, E-drop policy has the lowest number of message dropped among all the drop policies. Its maximum number of message dropped is 6872 at buffer size 2MB and its minimum number of message dropped is 845 at buffer size 10MB. 

• In Prophet routing protocol, E-drop 

policies have least number of messages dropped as compared to other drop policies. 

 

 

 

 

 

 

 

 

 

80 

 

60 

 

40 

 

20 

 

0 

Drop Random 

DLR 

MOFO 

E-Drop 
15000 

10000 

5000 

0 

2 4 6 8 10 

Varying Buffer Size 

3000
0 

2500

0 

2000

0 

Drop 
Random 

DLR 

MOF

O 

E-Drop 



 

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CTMJ | traditionalmedicinejournals.com                                    Chinese Traditional Medicine Journal | 2021 | Vol4 |Issue3 

 
 

 

 

 

Fig. 2. NMD vs. Varying in Buffer Size 

 Overhead Ratio (OHR) 

The following results are evaluated from figure 3. 

• In prophet routing protocol, the 

overhead ratio is minimum with increasing 

buffer size because the nodes in the network 

are not required to perform more 

computations to take decision which message 

to be accommodate in buffer capacity. 

• Overhead ratio of E-Drop policy is 

approximately equal with increasing the 

buffer size. 

• Overhead ratio of E-Drop policies is 

lesser as compared other drop policies. 

 

 

 

 

 

 

 

 

 

 

 

 

 

Average Delivery Latency 

The following points are analyzed from the fig 

4. 

• In Prophet routing protocol, the 

average delivery latency of the entire drop 

policies are gradually decreases with 

increasing buffer size due to flooding behavior 

of protocol. 

• The variation between maximum and 

minimum average delivery latency in case of 

Drop Random, DLR, MOFO and E- Drop 

policies are 24.18%, 17.49%, 27.74% and 

141.57% respectively. 

• E-drop policies are performed better 

among all other drop policies. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

6. Conclusion 

  

Fig. 4. ADL vs. Varying in Buffer Size 

  

In this paper, the performance of buffer management drop policies such as Drop Random DLR, 

MOFO and E-Drop are evaluated on Prophet 

routing protocol using ONE simulator. It has 

examined form the simulation that E-Drop 

strategy performs outstanding as compared 

to Drop Random, DLR and MOFO policies on 

Prophet routing protocol. The delivery 

probability of E-Drop strategy is improves 

29.68 % over Drop Random, 22.24% over DLR 

and 10% over MOFO policies with varying 

buffer size. 

 

References 

300 

250 

200 

150 

100 

50 

0 

Drop Random 

DLR 

MOFO 

E-Drop 2 4 6 8 10 

Varying Buffer Size 

7000 

6000 

5000 

4000 

3000 

2000 

1000 

0 

Drop Random 

DLR 

MOFO 

E-Drop 2 4 6 8 10 

Varying Buffer Size 



 

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CTMJ | traditionalmedicinejournals.com                                    Chinese Traditional Medicine Journal | 2021 | Vol4 |Issue3 

 
 

[1] K. Fall, “A Delay-Tolerant Network 

Architecture for Challenged Internets.” Proc. 

On Applications, Technologies, Architectures 

and Protocols for Computer Communications 

(SIGCOMM), New York, USA, (2003), 27–34. 

[2] A. Vahdat and D. Becker, “Epidemic 

routing for partially connected ad hoc 

networks.” Technical report, CS, Duke 

University, (2000). 

[3] T. Spyropoulos and K. Psounis. et al., 

“Spray and wait: an efficient routing scheme 

for intermittently connected mobile 

networks.” WDTN’05, New York, NY, USA, 

(2005), 252–259. 

[4] S. D. Han and Y. W. Chung, “An 

improved PRoPHET routing protocol in delay 

tolerant network.” The Scientific World 

Journal. (2015). 1-7. 

[5] M. Naziruddin, “Impact of Queuing 

Policy Variations on MaxProp DTN Routing 

Protocol.” Int’l J. of Comp. Sci. and Info. Tech. 

(IJCSIT). Vol 5 no. 6, (2014), 7841-7843. 

[6] S. Rashid, and A. H. Abdullah, et al., 

“E-DROP: An Effective Drop Buffer 

Management Policy for DTN Routing 

Protocols.” IJCA. Vol. 13 no.7, (2011), 8-13. 

[7] M. P. Rodrigues and N. Magaia, “Drop 

Policies for DTN Routing Protocols with 

Delivery Probability Estimation.” Journal on 

Adv. in Theory and Application Informatics, 

Vol. 3 no.1, (2017), 16-24. 

[8] J. Shen and W. L. M. Jin, et al., 

“Improvement of Buffer Scheme for Delay 

Tolerant Networks, Inno. in Theory Computer 

Science (ITCS), vol. 25, (2013), 384-390. 

[9] A. Lindgreny and A Doria, et al., 

“Poster: Probabilistic Routing in Intermittently 

Connected Networks.” ACM International 

Symposium on Mobile Ad Hoc Networking 

and Computing, (2003). 

[10] V. K. Samyal and S. S. Bhamber, el al., 

“Performance Evaluation of Delay Tolerant 

Network Routing Protocols,” Proc. 

International Journal of Computer 

Applications, (2015), 24-27. 

[11] A. Krifa, and C. Barakat,, et al., “An 

optimal joint scheduling and drop policy for 

Delay Tolerant Networks.” IEEE International 

Symposium on World of Wireless, Mobile and 

Multimedia Networks, Newport Beach, CA, 

(2008), 1-6. 

[12] V. K. Samyal and Y. K. Sharma, 

“Impact of Buffer Size on Different Drop 

Policies (DLR, MOFO and E-Drop) for MaxProp 

Routing Protocol in DTN.” International 

Journal for Research in Applied Science & 

Engineering Technology, vol. 6 no 6, (2018), 

1420-1424. 

[13] V. K Samyal and N.Gupta, 

“Comparison of MOFO Drop policy with New 

Efficient Buffer Management Policy.” 

International Journal of Innovative Research & 

Studies, vol. 8 no. 4, (2018), 456-460. 


