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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
31Zhejiang University of Science & Technology, Hangzhou 310023, China
2Lishui Radio and Television University, Lishui 323000, China
3Key Lab of E-Business and Information Security, Hangzhou Normal University, Hangzhou 310023, 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 alternative(s) 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 be- come 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.
Email addresses: [email protected] (Jiehui JU), [email protected] (Fuwei FAN).
1553–9105 / Copyright © 2013 Binary Information Press DOI: 10.12733/jcis6331
July 15, 2013
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 infor- mation. 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 Net-
work Route Security Evaluation with 2-tuple Linguistic
Information
Let A ={A1, A2,· · · , Am} be a discrete set of alternatives, and G = {G1, G2,· · · , Gn} be the set of attributes, w = (w1, w2,· · · , wn) is the weighting vector of the attributes Gj(j = 1, 2,· · · , n), where wj ∈ [0, 1], ∑n
j=1wj = 1. Suppose that ˜R =(
˜ rij)
m×n is the decision matrix, where ˜rij ∈ ˜S is a preference value, which takes the form of linguistic variables, for the alternative Ai ∈ A with respect to the attribute Gj ∈ 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 = (rij)m×n into 2-tuple linguistic decision matrix ˜R = (rij, 0)m×n.
Step 2 Defining the TLPIS and TLNIS as (r+, a+)
=((
r1+, a+1) ,(
r2+, a+2)
,· · · ,(
rn+, a+n))
(1) (r−, a−)
=((
r1−, a−1) ,(
r2−, a−2)
,· · · ,(
rn−, a−n))
(2) where
(r+j , a+j )
= max
i {(rij, aij)}, j = 1, 2, · · · , n. (
r−j , a−j)
= min
i {(rij, aij)}, j = 1, 2, · · · , n.
Step 3 Calculating the distances of each alternative from TLPIS and TLNIS using the following equation, respectively:
(ξi+, ηi+)
= ∆ ( n
∑
j=1
∆−1(rij, aij)− ∆−1(
r+j , a+j ) wj )
(3)
(ξi−, ηi−)
= ∆ ( n
∑
j=1
∆−1(rij, aij)− ∆−1(
r−j , a−j ) wj
)
(4)
Step 4 Calculating the relative closeness degree of each alternative from TLPIS using the fol- lowing equation
(ξi, ηi) = ∆
( ∆−1(
ξi−, ηi−)
∆−1(
ξi+, ηi+)
+ ∆−1(
ξi−, η−i ) )
, i = 1, 2,· · · , m. (5)
Step 5 According to the relative closeness degree (ξi, ηi), the ranking order of all alternatives can be determined. If any alternative has the highest (ξi, ηi) 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 Ai(i = 1, 2, 3, 4, 5) to select. The company selects four attribute to evaluate the five possible P2P network route systems: (1) G1 is the tactics; (2) G2 is the technology; (3) G3 is the economy; (4) G4 is the logistics and strategy. The five possible P2P network route systems Ai(i = 1, 2,· · · , 5) are to be evaluated using the linguistic term set
S ={s0 = extremely poor(EP ), s1 = very poor(V P ), s2 = poor(P ), s3 = medium(M ), s4 = good(G), s5 = very good(V G), s6 = extremely good(EG)}
by the decision makers under the above four attributes, as listed in the following matrix:
G1 G2 G3 G4
R = A1 A2
A3 A4 A5
s4 s6 s5 s5 s2 s3 s4 s3
s3 s5 s3 s4 s5 s4 s5 s2 s4 s3 s1 s3
And WT = (0.2, 0.4, 0.1, 0.3) is the weighting vector of the attributes Gj(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 = (rij)m×n into 2-tuple linguistic decision
matrix ˜R = (rij, 0)m×n .
G1 G2 G3 G4
R = A1 A2 A3 A4 A5
(s4, 0) (s6, 0) (s5, 0) (s5, 0) (s2, 0) (s3, 0) (s4, 0) (s3, 0) (s3, 0) (s5, 0) (s3, 0) (s4, 0) (s5, 0) (s4, 0) (s5, 0) (s2, 0) (s4, 0) (s3, 0) (s1, 0) (s3, 0)
Step 2 Defining the TLPIS and TLNIS as (r+, a+)
= ((s5, 0) , (s6, 0) , (s5, 0) , (s5, 0))T (r−, a−)
= ((s2, 0) , (s3, 0) , (s1, 0) , (s2, 0))T
Step 3 Calculating the distances of each P2P network route systems from TLPIS and TLNIS (ξ1+, η1+)
= (s2, 0.13) ,(
ξ2+, η2+)
= (s1, 0.32) (ξ3+, η3+)
= (s2, 0.26) ,(
ξ4+, η4+)
= (s2,−0.21) (ξ5+, η5+)
= (s2,−0.12) ,(
ξ1−, η1−)
= (s2,−0.26) (ξ2−, η2−)
= (s3,−0.43) ,(
ξ3−, η3−)
= (s2,−0.15) (ξ4−, η4−)
= (s2, 0.31) ,(
ξ5−, η5−)
= (s2, 0.37)
Step 4 Calculating the relative closeness degree of each P2P network route systems from TLPIS (ξ1, η1) = (s0, 0.25) , (ξ2, η2) = (s1,−0.31)
(ξ3, η3) = (s0, 0.46) , (ξ4, η4) = (s1,−0.34) (ξ5, η5) = (s1,−0.37)
Step 5 Ranking all the P2P network route systems Ai(i = 1, 2,· · · , 5) in accordance with the relative closeness degree (ξi, ηi): A2 ≻ A4 ≻ A5 ≻ A3 ≻ A1, and thus the most desirable P2P network route systems is A2.
4 Conclusions
In this paper, we investigate the multiple attribute decision making problems to deal with evalu- ation 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 alternative(s) is determined by calculating the shortest distance from the 2-tuple linguistic positive ideal solution (TLPIS) and on the other side the far- thest 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 key technology for P2P network route security evaluation is used to illustrate the applicability and effectiveness of the proposed model.
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