Trust Evaluation and Prioritization of Cloud Service Providers Using MADM Methods

Suruchi M Pawar, Eunice Grace Paulson, Prajakta Sunil Badgujar, Shilpa Deshpande
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Abstract

With the increasing market for cloud computing and the variety of Cloud Service Providers (CSPs) becoming available, making an appropriate choice of a CSP turns out to be challenging for the consumer. In order to cater to the user’s specific needs of quality, the services provided need to be user-centric. Trust plays an important role in the selection of cloud providers by users. This paper proposes CSP Trust evaluation, Prioritization and Recommendation System (CTPRS) for evaluating the trust of CSPs based on Quality of Service (QoS) parameters, and accordingly ranking and recommending them. MADM methods, namely ARAS, DEA, and GRA are used to evaluate trust by considering the user's preferences across multiple QoS parameters of CSPs. Comparative analysis of all three MADM methods is done using rank conformance, rank correlation, sensitivity, and computational complexity analysis. Experimental results demonstrate that GRA is superior to the other two methods. Thus, GRA is found to be the most suitable method and is therefore used for evaluating trust in CTPRS.
基于MADM方法的云服务提供商信任评估与优先级排序
随着云计算市场的不断增长和各种云服务提供商(CSP)的出现,对消费者来说,选择合适的CSP是一项挑战。为了迎合用户对质量的特定需求,所提供的服务需要以用户为中心。信任在用户选择云提供商的过程中起着重要的作用。本文提出了基于服务质量(QoS)参数的CSP信任评估、优先排序和推荐系统(CTPRS),用于评估CSP的信任,并对其进行排序和推荐。采用MADM方法,即ARAS、DEA和GRA,通过考虑用户对csp多个QoS参数的偏好来评估信任。通过秩一致性、秩相关性、灵敏度和计算复杂度分析,对三种MADM方法进行了比较分析。实验结果表明,GRA算法优于其他两种方法。因此,发现GRA是最合适的方法,因此用于评估CTPRS中的信任。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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