Cloud Provider Selection Based on Accountability and Security Using Interval-Valued Fuzzy TOPSIS

IF 0.6 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS International Journal of Decision Support System Technology Pub Date : 2022-01-01 DOI:10.4018/ijdsst.286684
T. Thasni, C. Kalaiarasan, K. Venkatesh
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引用次数: 2

Abstract

Cloud computing enables on-demand access to a public resource pool. Many businesses are migrating to the cloud due to its popularity and financial benefits. As a result, finding a suitable and best Cloud Service Provider is a difficult task for all cloud users. Many ranking systems, such as ANP, AHP and TOPSIS, have been proposed in the literature .However, many of the studies concentrated on quantitative data. But qualitative attributes are equally significant in many applications where the user is more concerned with the qualitative features.The implementation of MCDM approach for the ranking and the selection of the best player in the market as per the qualitative need of the cloud users like business organization or cloud brokers is the aim of this article. An ISO approved standard SMI framework is available for the evaluation of the CSPs.The authors have considered SMI attributes like accountability and security as the criteria for evaluation of the CSPs. The MCDM approach called IVF-TOPSIS that can handle the inherent vagueness in the cloud dataset is implemented in this work
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基于区间值模糊TOPSIS的可靠性和安全性的云提供商选择
云计算支持按需访问公共资源池。由于云的普及和经济效益,许多企业正在迁移到云。因此,找到一个合适的和最好的云服务提供商对所有云用户来说都是一项艰巨的任务。文献中提出了许多排序系统,如ANP、AHP和TOPSIS,但许多研究都集中在定量数据上。但是,在许多用户更关心定性特征的应用程序中,定性属性也同样重要。本文的目的是根据商业组织或云代理等云用户的定性需求,实施MCDM方法进行排名和选择市场上最好的参与者。ISO批准的标准SMI框架可用于评估csp。作者考虑了SMI属性,如问责制和安全性作为评估csp的标准。本文实现了一种名为IVF-TOPSIS的MCDM方法,该方法可以处理云数据集中固有的模糊性
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来源期刊
International Journal of Decision Support System Technology
International Journal of Decision Support System Technology COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
2.20
自引率
18.20%
发文量
40
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