CHEMICAL ENGINEERINGTRANSACTIONS VOL. 51, 2016 A publication of The Italian Association of Chemical Engineering Online at www.aidic.it/cet Guest Editors:Tichun Wang, Hongyang Zhang, Lei Tian Copyright © 2016, AIDIC Servizi S.r.l., ISBN978-88-95608-43-3; ISSN 2283-9216 The Computer Network Reliability Evaluation Research Ning Yu Weifang University of Science and Technology, Shouguang,Shandong, CHINA 7087370@qq.com Computer network reliability receives much concern. People's life has been inseparable from computer network. In this paper, according to the determined selection principles of computer network reliability evaluation indexes, 5 first-level indexes and 19 second-level indexes are selected to structure the computer network reliability evaluation system. Using the analytic hierarchy process (AHP) to determine the weight of each index, computer network reliability can be divided into five levels, that is, very reliable, reliable, general, poor, and very poor. Through expert evaluation, fuzzy mathematical evaluation model is established and the simulation experiment was carried out. The fuzzy mathematical evaluation model of computer network reliability is professional, scientific, and reasonable, which provides theoretical basis for the development of computer network. 1. Introduction With the development of society and the progress of science and technology, computers and mobile phones are widely popularized. Network has been applied in various fields. Network appears everywhere in current life(Adnen Sanaa, Samir Ben Abid, Abdennacer Boulila, Chokri Messaoud, Mohamed Boussaid, Najeh Ben Fadhel.2016). People are inseparable from the network now. As the users’ dependence on the network grows, the requirement for computer network reliability people demand is higher and higher. If there appear problems on computer network, people's daily life, national economy, and even social stability will be affected a lot. The reliability of network system is a computer discipline. Its task is to carry on the statistical analysis to the network system faults in certain time, under certain conditions and a certain function, to find out rules, by means of mathematical methods to synthesize, analyse and describe network system regularly, selecting the appropriate data to analyse computer network reliability(Chuan-sheng Xie, et.al. 2010). Reliability is an important performance index of network evaluation. With the wide application of computers in various fields, the importance of computer network reliability becomes clear. A specialized network system reliability study is gradually formed. The necessary tools that be used are reliability mathematics which includes fuzzy mathematics, probability statistics, graph theory, optimization decision and topology, etc (Michal Przewozniczek.2016). Since the 1990s, computer network system reliability becomes a new research hotspot gradually. Traffic network, logistics network, power network, and transport network are associated with computer network. And its evaluation problems are more and more paid attention to. In this paper, on the basis of previous research, the evaluation index system of computer network reliability is first determined and then fuzzy mathematical evaluation model of computer network reliability is established(Mohammad Sadeq Garshasbi.2016). 2. The establishment of computer network reliability evaluation index system The computer network reliability evaluation is tedious work, which need to fully consider the influencing factors of computer network, not only the fixed indexes, but change indexes as well. In the process of selecting evaluation indexes, certain principles should be followed(Ahmad Jakalan, Jian Gong, Qi Su, Xiaoyan Hu, Abdeldime M.S. Abdelgder.2016). The detailed principles are as follows: (1)The combination of overall consideration and an emphasis In the process of selecting computer network reliability evaluation indexes, not only each main index that influences computer network should be fully considered, but also the outburst indexes that influence computer DOI: 10.3303/CET1651100 Please cite this article as: Yu N., 2016, The computer network reliability evaluation research, Chemical Engineering Transactions, 51, 595-600 DOI:10.3303/CET1651100 595 http://scholar.cnki.net/result.aspx?q=%e4%bd%9c%e8%80%85%3a(Adnen+Sanaa)&uid=WEEvREcwSlJHSldRa1FiNDEwTkordlhhYTBJb0xTcVFUemJCMVlKcTg3R1YxL3ZSWGU0Ti9FQWdidXpocUliaWhRPT0=$9A4hF_YAuvQ5obgVAqNKPCYcEjKensW4IQMovwHtwkF4VYPoHbKxJw!!&UID=WEEvREcwSlJHSldRa1FiNDEwTkordlhhYTBJb0xTcVFUemJCMVlKcTg3R1YxL3ZSWGU0Ti9FQWdidXpocUliaWhRPT0=$9A4hF_YAuvQ5obgVAqNKPCYcEjKensW4IQMovwHtwkF4VYPoHbKxJw!! http://scholar.cnki.net/result.aspx?q=%e4%bd%9c%e8%80%85%3a(Samir+Ben+Abid)&uid=WEEvREcwSlJHSldRa1FiNDEwTkordlhhYTBJb0xTcVFUemJCMVlKcTg3R1YxL3ZSWGU0Ti9FQWdidXpocUliaWhRPT0=$9A4hF_YAuvQ5obgVAqNKPCYcEjKensW4IQMovwHtwkF4VYPoHbKxJw!! http://scholar.cnki.net/result.aspx?q=%e4%bd%9c%e8%80%85%3a(Abdennacer+Boulila)&uid=WEEvREcwSlJHSldRa1FiNDEwTkordlhhYTBJb0xTcVFUemJCMVlKcTg3R1YxL3ZSWGU0Ti9FQWdidXpocUliaWhRPT0=$9A4hF_YAuvQ5obgVAqNKPCYcEjKensW4IQMovwHtwkF4VYPoHbKxJw!! http://scholar.cnki.net/result.aspx?q=%e4%bd%9c%e8%80%85%3a(Chokri+Messaoud)&uid=WEEvREcwSlJHSldRa1FiNDEwTkordlhhYTBJb0xTcVFUemJCMVlKcTg3R1YxL3ZSWGU0Ti9FQWdidXpocUliaWhRPT0=$9A4hF_YAuvQ5obgVAqNKPCYcEjKensW4IQMovwHtwkF4VYPoHbKxJw!! http://scholar.cnki.net/result.aspx?q=%e4%bd%9c%e8%80%85%3a(Mohamed+Boussaid)&uid=WEEvREcwSlJHSldRa1FiNDEwTkordlhhYTBJb0xTcVFUemJCMVlKcTg3R1YxL3ZSWGU0Ti9FQWdidXpocUliaWhRPT0=$9A4hF_YAuvQ5obgVAqNKPCYcEjKensW4IQMovwHtwkF4VYPoHbKxJw!! http://scholar.cnki.net/result.aspx?q=%e4%bd%9c%e8%80%85%3a(Najeh+Ben+Fadhel)&uid=WEEvREcwSlJHSldRa1FiNDEwTkordlhhYTBJb0xTcVFUemJCMVlKcTg3R1YxL3ZSWGU0Ti9FQWdidXpocUliaWhRPT0=$9A4hF_YAuvQ5obgVAqNKPCYcEjKensW4IQMovwHtwkF4VYPoHbKxJw!!&UID=WEEvREcwSlJHSldRa1FiNDEwTkordlhhYTBJb0xTcVFUemJCMVlKcTg3R1YxL3ZSWGU0Ti9FQWdidXpocUliaWhRPT0=$9A4hF_YAuvQ5obgVAqNKPCYcEjKensW4IQMovwHtwkF4VYPoHbKxJw!! 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That is, overall consideration should be combined with an emphasis. (2)The combination of accuracy evaluation and fuzzy evaluation In the process of selecting computer network reliability evaluation indexes, most indexes need accurate data, according to its data to evaluate computer network reliability. Some indexes haven’t got accurate data. But we need to clear the evaluation direction or trend. Therefore, it is necessary to combine the accuracy evaluation with fuzzy evaluation. (3)The combination of operability and systematization In the process of selecting computer network reliability evaluation indexes, the final evaluation indexes that have been determined must be operable. Thus, the evaluation indexes are required to be simple, practical, and amortizable. At the same time, the integrity and systematization of computer network reliability evaluation system should be considered, combining the operability with the systematization. According to the three principles determining computer network reliability evaluation indexes above, based on a large number of document data, the 5 first-level indexes and 19 second-level indexes of computer network reliability evaluation index system could be determined. The detailed indexes are shown in table 1. Table 1: computer network reliability evaluation index system computer network reliability evaluation P first-level indexes second-level indexes physical performance A the standardization of interface A1 electrical operability A 2 communication exchange equipment A 3 communication link A 4 link performance B the efficiency of data transmission B1 link utilization ratio B2 link transmission ability B3 data transfer success ratio B4 network performance C network connectivity C 1 network vulnerability C 2 network transmitting coefficient C 3 network accessibility C4 transmission performance D total transmission D1 transmission delay D2 transmission pipeline D3 maximum transmission D4 user performance E user number E1 user usage time E2 network knowledge of users E3 3. The introduction of fuzzy mathematics level evaluation method(Li Tao.2015) The fuzzy mathematics level evaluation method is a common method in fuzzy decision problems, which is a comprehensive evaluation method to the object affected by multiple evaluation indexes based on fuzzy mathematics. The aim is using fuzzy mathematics knowledge system to determine the factor set and evaluation set of all evaluation indexes, to structure level evaluation matrix and to determine the evaluation level of the object so as to make overall evaluation to evaluated object. (1)Determine evaluation index factor set  1 2, , , nP p p p , and there are n kinds of evaluated objects. (2)Determine level evaluation set  1 2, , , mV v v v , and m is the level number of evaluation. (3)Determine fuzzy evaluation matrix ( ) ij n m R r   , and the basic steps are as follows: First, make a level evaluation ( )f p (and 1, 2, ,i n ) to all index factors p , we could get a fuzzy mapping f from P to V , namely: 1 2 : ( ), ( ) ( , , , ) ( ) i i i i im f P F P p f p r r r F V    Second, from the fuzzy mapping f , we could induce the fuzzy relation ( ) f R F P V  , namely: ( , ) ( )( ) f i i i i ij R p v f p v r  , and 1, 2, ,i n ; 1, 2, ,j m , Therefore, fuzzy evaluation matrix ( ) ij n m R r   could be determined. (4)The analytic hierarchy process (AHP) is used to determine the weights of evaluation indexes at all levels. 596 (5)According to the weights of each evaluation index and evaluation matrix, use the matrix multiplication to get the comprehensive evaluation vector Tw R . 4. The fuzzy mathematics model of computer network reliability evaluation(Han Zhonggeng.2005) (1)According to table 1, the evaluation index factor set of computer network reliability evaluation  1 2 19, , ,P p p p could be determined. And there are 19 evaluation indexes of the evaluated object. Meanwhile, draw the hierarchical structure diagram of computer network reliability evaluation. The specific details are shown in diagram 1. Table 2: the second-level evaluation index classification of computer network reliability second-level index level the standardization of interface A1 very standard standard general less standard nonstandard electrical operabilityA2 well-operated operated general difficult to operate very difficult to operate communication exchange equipment A3 very good good general poor very poor communication link A4 well integrated integrate d general not integrated damaged the efficiency of data transmission B1 very high high general low very low link utilization ratio B2 very high high general low very low link transmission ability B3 very big big general small very small data transfer success ratio B4 very high high general low very low network connectivity C1 very good good general poor very poor network vulnerability C2 very strong strong general vulnerable very vulnerable network transmitting coefficient C3 very big big general small very small network accessibility C4 very good good general poor very poor total transmission D1 very big big general small very small transmission delay D2 very good good general poor very poor transmission pipeline D3 very good good general poor very poor maximum transmission D4 very big big general small very small user number E1 few a few general many a lot user usage time E2 little a little general much a lot network knowledge of users E3 very good good general poor very poor (2)Determine the level evaluation set of computer network reliability evaluation  1 2 5, , ,V v v v ,the computer network reliability is divided into 5 levels, that is, very reliable, reliable, general, poor, and very poor(Li Tao.2015). The specific levels are shown in table 2. (3)Determine fuzzy evaluation matrix of computer network reliability evaluation ( ) ij n m R r   . Using the expert evaluation method, the level evaluation to the second-level indexes of computer network reliability evaluation is carried on. Here we choose the expert group composed of10 experts, and we could get: ( ) ( ) ( ) 11 12 15 ( ) ( ) ( ) 41 42 45 A A A A A A A r r r r r r R            , The expert number of j level ij r  10 . Similarly to the following conclusions: B R , C R , D R , E R . 597 Diagram 1: the hierarchical structure diagram of computer network reliability evaluation Table 3: each index weights of computer network reliability evaluation computer network reliability evaluation P first-level indexes weight second-level indexes weight physical performance A 0.0506 the standardization of interface A1 0.1154 electrical operabilityA2 0.5455 communication exchange equipment A3 0.1940 communication link A4 0.1451 link performance B 0.2339 the efficiency of data transmission B1 0.0931 link utilization ratio B2; 0.2452 link transmission ability B3 0.5050 data transfer success ratio B4 0.1567 network performance C 0.1285 network connectivity C1 0.6489 network vulnerability C2 0.0881 network transmitting coefficient C3 0.2178 network accessibility C4 0.0452 transmission performance D 0.0931 total transmission D1 0.1445 transmission delay D2 0.3705 transmission pipeline D3 0.4406 maximum transmission D4 0.0444 user performance E 0.4939 user number E1 0.6250 user usage time E2 0.1365 network knowledge of users E3 0.2385 (4)Determine each index weights of computer network reliability evaluation at all levels. The analytic hierarchy process (AHP) is used to calculate each index weights of computer network reliability evaluation at all levels. At the same time, consistency check is carried on. And the final weight results are shown in table 3. (5)According to each second-level index corresponding weights of computer network reliability evaluation, the 5 fuzzy evaluation matrixes of first-level indexes could be obtained as follows: ( ) T T T T T T P A A B B C C D D E E R R R R R R     , 598 According to the weights of first-level indexes, level evaluation vector of computer network reliability evaluation could be got as follows: T P P w R , Based on the maximum principle, the biggest component of w is the level of computer network reliability evaluation. 5. An empirical analysis of computer network reliability evaluation 10 experts evaluate the computer network reliability of Weifang University of Science and Technology. 19 second-level evaluation indexes are carried on the fuzzy level evaluation (SiShouKui Sun Zhaoliang.2015). The detailed results are shown in table 4. Table 4: the second-level index level evaluation results of computer network reliability of Weifang University of Science and Technology second-level indexes level the standardization of interface A1 0 2 6 2 0 electrical operabilityA2 1 2 4 2 1 communication exchange equipment A 3 1 3 3 2 1 communication link A4 0 2 4 3 1 the efficiency of data transmission B1 0 2 5 2 1 link utilization ratio B2 0 1 7 1 1 link transmission ability B3 2 4 4 0 0 data transfer success ratio B4 5 3 2 0 0 network connectivity C1 3 5 1 1 0 network vulnerability C2 1 3 5 1 0 network transmitting coefficient C3 4 3 3 0 0 network accessibility C4 1 2 4 3 0 total transmission D1 0 2 6 1 1 transmission delay D2 4 5 1 0 0 transmission pipeline D3 2 4 3 1 0 maximum transmission D4 1 3 5 1 0 user number E1 2 3 4 1 0 user usage time E2 1 3 6 0 0 After doing the data processing to the expert evaluation results. Using the program MATLB (The specific details are shown in the attachment.), the evaluation vector of computer network reliability evaluation of Weifang University of Science and Technology is shown as follows:  0.2098 0.3081 0.3877 0.0807 0.0137w  , Based on the maximum principle we could get that the evaluation level of computer network reliability of Weifang University of Science and Technology is general. The results accord with the actual situation of computer network reliability of Weifang University of Science and Technology. Weifang University of Science and Technology is developing rapidly, but its computer network development is relatively slow, and its reliability and security should be further improved. 6. Conclusion It is feasible to use fuzzy mathematics knowledge to evaluate computer network reliability. From the application of this model, we could get that the 5 first-level indexes of computer network reliability of Weifang University of Science and Technology doesn’t coordinate well, especially the network performance is not good enough. In this paper, I suggest that this University should strengthen its management coordination through administration, market and technical means, change its computer network structure, and enhance its computer network reliability. 599 http://dict.cn/enhance Attachment Program MATLB a=load ('jsjwlkkxpg.txt'); w= [0.0506 0.2339 0.1285 0.0931 0.4939]; w1= [0.1154, 0.5455, 0.1940, 0.1451]; w2= [0.0931, 0.2452, 0.5050, 0.1567]; w3= [0.6489, 0.0881, 0.2178, 0.0452]; w4= [0.1445, 0.3705, 0.4406, 0.0444]; w5= [0.6250, 0.1365, 0.2385]; b(1,:)=w1*a([1:4],:); b(2,:)=w2*a([5:8],:); b (3,:)=w3*a([9:12],:); b (4,:)=w4*a([13:16],:); b (5,:)=w5*a([17:end],:); c=w*b c =0.2098 0.3081 0.3877 0.0807 0.0137 Reference Garshasbi M.S., 2016, Fault localization based on combines active and passive measurements in computer networks by ant colony optimization. Reliability Engineering and System Safety, DOI: 10.1016/j.ress.2016.03.017 Han Z.G., 2005, Mathematical modeling method and its application [M]. 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Xie C.S., Xu X., Hou W.T., Xu F.R., 2010, Path analysis and synthetic evaluation of city low carbon economy development [J], technical economy, (8): 29-32. 600 http://scholar.cnki.net/result.aspx?q=%e4%bd%9c%e8%80%85%3a(Mohammad+Sadeq+Garshasbi)&uid=WEEvREcwSlJHSldRa1FiNDEwTkordlhhYTBJb0xTcVFUemJCMVlKcTg3R1YxL3ZSWGU0Ti9FQWdidXpocUliaWhRPT0=$9A4hF_YAuvQ5obgVAqNKPCYcEjKensW4IQMovwHtwkF4VYPoHbKxJw!!&UID=WEEvREcwSlJHSldRa1FiNDEwTkordlhhYTBJb0xTcVFUemJCMVlKcTg3R1YxL3ZSWGU0Ti9FQWdidXpocUliaWhRPT0=$9A4hF_YAuvQ5obgVAqNKPCYcEjKensW4IQMovwHtwkF4VYPoHbKxJw!! http://d.scholar.cnki.net/link/doi/SJESTEMP_U/SJES1BDCBE392927EEB92FF13AFF8CC8BD81?UID=WEEvREcwSlJHSldRa1FiNDEwTkordlhhYTBJb0xTcVFUemJCMVlKcTg3R1YxL3ZSWGU0Ti9FQWdidXpocUliaWhRPT0=$9A4hF_YAuvQ5obgVAqNKPCYcEjKensW4IQMovwHtwkF4VYPoHbKxJw!! http://scholar.cnki.net/result.aspx?q=%e4%bd%9c%e8%80%85%3a(Ahmad+Jakalan)&uid=WEEvREcwSlJHSldRa1FiNDEwTkordlhhYTBJb0xTcVFUemJCMVlKcTg3R1YxL3ZSWGU0Ti9FQWdidXpocUliaWhRPT0=$9A4hF_YAuvQ5obgVAqNKPCYcEjKensW4IQMovwHtwkF4VYPoHbKxJw!!&UID=WEEvREcwSlJHSldRa1FiNDEwTkordlhhYTBJb0xTcVFUemJCMVlKcTg3R1YxL3ZSWGU0Ti9FQWdidXpocUliaWhRPT0=$9A4hF_YAuvQ5obgVAqNKPCYcEjKensW4IQMovwHtwkF4VYPoHbKxJw!! 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