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

Authors

DOI:

https://doi.org/10.9781/ijimai.2017.12.001

Keywords:

AHP, COPRAS, SAW, Spearman’s Rank Correlation Coefficient, TOPSIS, VIKOR
Supporting Agencies
The authors express their gratitude to E. Al-Masri and Q. H. Mahmoud for providing the QWS dataset which has supported this research to evaluate MCDM methods on well-validated web services based on different Quality of Service parameters.

Abstract

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.

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Published

2019-03-01
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How to Cite

Bagga, P., Joshi, A., and Hans, R. (2019). QoS based Web Service Selection and Multi-Criteria Decision Making Methods. International Journal of Interactive Multimedia and Artificial Intelligence, 5(4), 113–121. https://doi.org/10.9781/ijimai.2017.12.001

Issue

Vol. 5 No. 4 (2019): IJIMAI 2019 - Special Issue on Artificial Intelligence Applications.

Section

Regular Articles