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Book ChapterDOI

A QoS-Aware Hybrid TOPSIS–Plurality Method for Multi-criteria Decision Model in Mobile Cloud Service Selection

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TLDR
The proposed system suggests a hybrid based on TOPSIS algorithm and plurality voting method which is more efficient, trustable for selecting the best cloud services.
Abstract
The business framework architecture and evaluation are changing the growth of mobile cloud computing (MCC). The business service users required the facilities for selecting the mobile cloud services according to their quality of service (QoS) values in the business environment. In such a business environment, QoS parameter values help to build consumer confidence and provide a reliable environment for them. So the proposed system suggests a hybrid based on TOPSIS algorithm and plurality voting method which is more efficient, trustable for selecting the best cloud services. This algorithm has three phases to identify the service in the ranking process. The first phase is used to make a group the parameters based on the user’s requirements. The second phase applied the TOPSIS method on each of the parameters to get the service ranking. The final phase employed the plurality method which is counted the voting for each service to determine the best services. The hybrid algorithm takes O(n2) time in the best service selection process which is better than existing popular AHP, ANP multi-criteria decision methods in terms of time complexity.

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Citations
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Journal ArticleDOI

Service Selection Using Multi-criteria Decision Making: A Comprehensive Overview

TL;DR: This paper provides an extensive investigation of the state of the art MCDM-based service selection schemes proposed in the literature and provides the required background knowledge and puts forward a taxonomy of the investigatedservice selection schemes regarding their applied M CDM methods.
Book ChapterDOI

An Efficient Approach for Selecting QoS-Based Web Service Machine Learning Models Using Topsis

TL;DR: Several automatic learning models are proposed to classify web services in categories according to QoS attributes using a refined data set, then select the best model based on performance criteria through the TOPSIS method.
References
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Journal ArticleDOI

Multi-criteria decision making approaches for supplier evaluation and selection: A literature review

TL;DR: Evidence is provided that the multi-criteria decision making approaches are better than the traditional cost-based approach, but also aids the researchers and decision makers in applying the approaches effectively.
Journal ArticleDOI

A framework for ranking of cloud computing services

TL;DR: This work proposes a framework and a mechanism that measure the quality and prioritize Cloud services and will create healthy competition among Cloud providers to satisfy their Service Level Agreement (SLA) and improve their QoS.
Journal ArticleDOI

Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment

TL;DR: It is shown that the proposed fuzzy TOPSIS method performs better than the other fuzzy versions of the TOPSis method.
Journal ArticleDOI

State of art surveys of overviews on MCDM/MADM methods

TL;DR: There is a need for research to study the strengths and weaknesses of different decision-making methods, as the situation with reviews of MCDM/MADM methods is described.
Proceedings ArticleDOI

QoS-based Discovery and Ranking of Web Services

TL;DR: The Web service relevancy function (WsRF) used for measuring the relevancies ranking of a particular Web service based on client's preferences, and QoS metrics is introduced and presented.
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