Analysis of Model and Key Technology for P2P Network Route Security Evaluation with 2-tuple Linguistic Information

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1 Journal of Computational Information Systems 9: Available at Analysis of Model and Key Technology for P2P Network Route Security Evaluation with 2-tuple Linguistic Information Jiehui JU 1, Fuwei FAN 2,, Jiyi WU 3 1 Zhejiang University of Science & Technology, Hangzhou , China 2 Lishui Radio and Television University, Lishui , China 3 Key Lab of E-Business and Information Security, Hangzhou Normal University, Hangzhou , China Abstract In this paper, we investigate the multiple attribute decision making problems to evaluate the key technology for P2P network route security with 2-tuple linguistic information. We extended the TOPSIS model to solve the evaluation problems of key technology for P2P network route security with 2-tuple linguistic information. According to the traditional ideas of TOPSIS, the optimal alternatives is determined by calculating the shortest distance from the 2-tuple linguistic positive ideal solution TLPIS and on the other side the farthest distance of the 2-tuple linguistic negative ideal solution TLNIS. It is based on the concept that the optimal alternative should have the shortest distance from the positive ideal solution and on the other side the farthest distance of the negative ideal solution. The method has exact characteristic in linguistic information processing. It avoided information distortion and losing which occur formerly in the linguistic information processing. Finally, a numerical example with the key technology for P2P network route security evaluation is used to illustrate the applicability and effectiveness of the proposed model. Keywords: Multiple Attribute Decision Making; TOPSIS Model; 2-Tuple; P2P Network Route Security 1 Introduction As the process of human economy and social intellectualization speeding up, knowledge has become the most important resources in modern society [1-6]. Enterprises operation pattern has shifted from product-oriented to development of human capital and intellectual resources, how to effectively manage and apply the knowledge resources, integrate the existing knowledge and get access to new knowledge, has become the key point to gain the competitive advantage [7-10]. The evaluation of knowledge management is the beginning of effective knowledge management and throughout the process of knowledge management. Whether to evaluate the effective knowledge Corresponding author. addresses: @qq.com Jiehui JU, @qq.com Fuwei FAN / Copyright 2013 Binary Information Press DOI: /jcis6331 July 15, 2013

2 5530 J. Ju et al. /Journal of Computational Information Systems 9: management, continual feeding back and improve in the process of knowledge management based on the assessment result, immediately have an influence on efficiency and effect of enterprise knowledge management implementation [11-15]. The aim of this paper is to develop a TOPSIS model for key technology for P2P network route security evaluation with 2-tuple linguistic information. The remainder of this paper is set out as follows. In the next section, we introduce the basic concepts of traditional TOPSIS model. In Section 3 we utilize the TOPSIS model to solve the key technology for P2P network route security evaluation with 2-tuple linguistic information. In Section 4, we give an illustrative example to verify the developed approach and to demonstrate its feasibility and practicality. In Section 5 we conclude the paper and give some remarks. 2 Analysis of Model and Key Technology for P2P Network Route Security Evaluation with 2-tuple Linguistic Information Let A = {A 1, A 2,, A m } be a discrete set of alternatives, and G = {G 1, G 2,, G n } be the set of attributes, w = w 1, w 2,, w n is the weighting vector of the attributes G j j = 1, 2,, n, where w j [0, 1], n j=1 w j = 1. Suppose that R = r ij m n is the decision matrix, where r ij S is a preference value, which takes the form of linguistic variables, for the alternative A i A with respect to the attribute G j G. In the following, we will extend the TOPSIS method [8, 9], to solve multiple attribute decision making problems to deal with evaluation model of key technology for P2P network route security evaluation with 2-tuple linguistic information. Step 1 Transforming linguistic decision matrix R = r ij m n matrix R = r ij, 0 m n. into 2-tuple linguistic decision Step 2 Defining the TLPIS and TLNIS as where r j, a j r, a = r 1, a 1, r 2, a 2,, r n, a n r, a = r1, a 1, r 2, a 2,, r n, a n = max {r ij, a ij }, j = 1, 2,, n. r j, a j = min {r ij, a ij }, j = 1, 2,, n. i i 1 2 Step 3 Calculating the distances of each alternative from TLPIS and TLNIS using the following equation, respectively: i, η i = n j=1 1 r ij, a ij 1 r j, a j wj 3 i, η i = n j=1 1 r ij, a ij 1 r j, a j wj 4

3 J. Ju et al. /Journal of Computational Information Systems 9: Step 4 Calculating the relative closeness degree of each alternative from TLPIS using the following equation 1 i i, η i =, η i 1 i, η i 1 i, η i, i = 1, 2,, m. 5 Step 5 According to the relative closeness degree i, η i, the ranking order of all alternatives can be determined. If any alternative has the highest i, η i value, then, it is the most desirable alternative. 3 Illustrative Example In the following, we present an illustrative example of the new approach in a decision making problem about key technology for P2P network route security evaluation. Suppose a company plans to evaluate the key technology for P2P network route security. There is a panel with five possible P2P network route systems A i i = 1, 2, 3, 4, 5 to select. The company selects four attribute to evaluate the five possible P2P network route systems: 1 G 1 is the tactics; 2 G 2 is the technology; 3 G 3 is the economy; 4 G 4 is the logistics and strategy. The five possible P2P network route systems A i i = 1, 2,, 5 are to be evaluated using the linguistic term set S = {s 0 = extremely poorep, s 1 = very poorv P, s 2 = poorp, s 3 = mediumm, s 4 = goodg, s 5 = very goodv G, s 6 = extremely goodeg} by the decision makers under the above four attributes, as listed in the following matrix: R = A 1 A 2 A 3 A 4 A 5 G 1 G 2 G 3 G 4 s 4 s 6 s 5 s 5 s 2 s 3 s 4 s 3 s 3 s 5 s 3 s 4 s 5 s 4 s 5 s 2 s 4 s 3 s 1 s 3 And W T = 0.2, 0.4, 0.1, 0.3 is the weighting vector of the attributes G j j = 1, 2, 3, 4. In the following, we shall utilize the proposed approach in this paper getting the most desirable P2P network route systems: Step 1 Transforming linguistic decision matrix R = r ij m n into 2-tuple linguistic decision

4 5532 J. Ju et al. /Journal of Computational Information Systems 9: matrix R = r ij, 0 m n. R = A 1 A 2 A 3 A 4 A 5 G 1 G 2 G 3 G 4 s 4, 0 s 6, 0 s 5, 0 s 5, 0 s 2, 0 s 3, 0 s 4, 0 s 3, 0 s 3, 0 s 5, 0 s 3, 0 s 4, 0 s 5, 0 s 4, 0 s 5, 0 s 2, 0 s 4, 0 s 3, 0 s 1, 0 s 3, 0 Step 2 Defining the TLPIS and TLNIS as r, a = s 5, 0, s 6, 0, s 5, 0, s 5, 0 T r, a = s 2, 0, s 3, 0, s 1, 0, s 2, 0 T Step 3 Calculating the distances of each P2P network route systems from TLPIS and TLNIS 1, η 1 = s2, 0.13, 2, η 2 = s1, , η 3 = s2, 0.26, 4, η 4 = s2, , η 5 = s2, 0.12, 1, η1 = s2, , η2 = s3, 0.43, 3, η3 = s2, , η4 = s2, 0.31, 5, η5 = s2, 0.37 Step 4 Calculating the relative closeness degree of each P2P network route systems from TLPIS 1, η 1 = s 0, 0.25, 2, η 2 = s 1, , η 3 = s 0, 0.46, 4, η 4 = s 1, , η 5 = s 1, 0.37 Step 5 Ranking all the P2P network route systems A i i = 1, 2,, 5 in accordance with the relative closeness degree i, η i : A 2 A 4 A 5 A 3 A 1, and thus the most desirable P2P network route systems is A 2. 4 Conclusions In this paper, we investigate the multiple attribute decision making problems to deal with evaluation model of key technology for P2P network route security evaluation with 2-tuple linguistic information. We extended the TOPSIS model to solve the evaluation problems of key technology for P2P network route security evaluation with 2-tuple linguistic information. According to the traditional ideas of TOPSIS, the optimal alternatives is determined by calculating the shortest distance from the 2-tuple linguistic positive ideal solution TLPIS and on the other side the farthest distance of the 2-tuple linguistic negative ideal solution TLNIS. It is based on the concept

5 J. Ju et al. /Journal of Computational Information Systems 9: that the optimal alternative should have the shortest distance from the positive ideal solution and on the other side the farthest distance of the negative ideal solution. The method has exact characteristic in linguistic information processing. It avoided information distortion and losing which occur formerly in the linguistic information processing. Finally, a numerical example with key technology for P2P network route security evaluation is used to illustrate the applicability and effectiveness of the proposed model. References [1] Xiaoyue Liu, Yanbing Ju, Aihua Wang, A Multiple Attribute Group Decision Making Method with its Application to Emergency Alternative Assessment, JCIT: Journal of Convergence Information Technology, Vol. 7, No. 2, pp , [2] Ming Li, Yanjing Zhang, The OWA-VIKOR method for multiple attributive group decision making in 2-tuple linguistic setting, JCIT: Journal of Convergence Information Technology, Vol. 7, No. 2, pp , [3] Rui Lin, Xiaofei Zhao, Hongjun Wang, Guiwu Wei, Model for Potential Evaluation of Emerging Technology Commercialization with Hesitant Fuzzy Information, IJACT: International Journal of Advancements in Computing Technology, Vol. 4, No. 1, pp , [4] Xiaorong Wang, Zhanhong Gao, Xiaofei Zhao, Guiwu Wei, Model for Evaluating the Government Archives Website s Construction Based on the GHFHWD Measure with Hesitant Fuzzy Information, JDCTA: International Journal of Digital Content Technology and its Applications, Vol. 5, No. 12, pp , [5] Xia Wang, Likun Peng, TOPSIS Method for Performance Appraisal in Liquor Industry Based on Economic Value Added, IJACT: International Journal of Advancements in Computing Technology, Vol. 4, No. 2, pp , [6] Ying Wang, An Approach to Software Selection with Triangular Intuitionistic Fuzzy Information, IJACT: International Journal of Advancements in Computing Technology, Vol. 4, No. 2, pp , [7] Hongxia Ruan, Xingrong Yan, Grey Relational Analysis Model for Evaluating the Enterprise s Financial Management, IJACT: International Journal of Advancements in Computing Technology, Vol. 4, No. 2, pp , [8] F. Herrera and L. Nartinez, A 2-tuple fuzzy linguistic representation model for computing with words, IEEE Transactions on Fuzzy Systems, Vol.8, No.6, pp , [9] F. Herrera and L. Martinez, A model based on linguistic 2-tuples for dealing with multigranularity hierarchical linguistic contexts in multiexpert decision-making, IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, Vol.31, No. 2, pp , [10] E. Herrera-Viedma, Modeling the retrieval process for an information retrieval system using an ordinal fuzzy linguistic approach, Journal of the American Society for Information Science and Technology, Vol. 52, No. 6, pp , [11] E. Herrera-Viedma, and A. G. Lopez-Herrera, A Review on Information Accessing Systems Based on Fuzzy Linguistic Modelling, International Journal of Computational Intelligence Systems, Vol. 3, No. 4, pp , [12] E. Herrera-Viedma, A. G. Lopez-Herrera, M. Luque et al., A fuzzy linguistic IRS model based on a 2-tuple fuzzy linguistic approach, International Journal of Uncertainty Fuzziness and Knowledge- Based Systems, Vol. 15, No. 2, pp , 2007.

6 5534 J. Ju et al. /Journal of Computational Information Systems 9: [13] Guiwu Wei, Some generalized aggregating operators with linguistic information and their application to multiple attribute group decision making, Computers & Industrial Engineering, Vol. 61, No. 1, pp , [14] Guiwu Wei, GRA method for multiple attribute decision making with incomplete weight information in intuitionistic fuzzy setting, Knowledge-Based Systems, Vol. 23, No. 3, pp , [15] Guiwu Wei, A method for multiple attribute group decision making based on the ET-WG and ET-OWG operators with 2-tuple linguistic information, Expert Systems with Applications, Vol. 37, No. 12, pp , 2010.