QoS based Web Service Selection and Multi-Criteria Decision Making Methods

被引:37
作者
Bagga, Pallavi [1 ]
Joshi, Aarchit [2 ]
Hans, Rahul [2 ]
机构
[1] Lovely Profess Univ, Dept Comp Sci & Engn, Phagwara, Punjab, India
[2] DAV Univ, Dept Comp Sci & Engn, Jalandhar, Punjab, India
来源
INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE | 2019年 / 5卷 / 04期
关键词
AHP; COPRAS; SAW; Spearman's Rank Correlation Coefficient; TOPSIS; VIKOR; FUZZY; RULES; MCDM; GIS; AHP;
D O I
10.9781/ijimai.2017.12.001
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the continuing proliferation of web services offering similar efficacies, around the globe, it has become a challenge for a user to select the best web service. In literature, this challenge is exhibited as a 0-1 knapsack problem of multiple dimensions and multiple choices, known as an NP-hard problem. Multi-Criteria Decision Making (MCDM) method is one of the ways which suits this problem and helps the users to select the best service based on his/her preferences. In this regard, this paper assists the researchers in two conducts: Firstly, to witness the performance of different MCDM methods for large number of alternatives and attributes. Secondly, to perceive the possible deviation in the ranking obtained from these methods. For carrying out the experimental evaluation, in this paper, five different well-known MCDM methods have been implemented and compared over two different scenarios of 50 as well as 100 web services, where their ranking is defined on an account of several Quality of Service (QoS) parameters. Additionally, a Spearman's Rank Correlation Coefficient has been calculated for different pairs of MCDM methods in order to provide a clear depiction of MCDM methods showing the least deviation in their ranking. The experimental results comfort web service users in conquering an appropriate decision on the selection of suitable service.
引用
收藏
页码:113 / 121
页数:9
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