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CCS-OSSR: A framework based on Hybrid MCDM for Optimal Service Selection and Ranking of Cloud Computing Services
Cluster Computing ( IF 4.4 ) Pub Date : 2020-08-05 , DOI: 10.1007/s10586-020-03166-3
Rakesh Ranjan Kumar , Binita Kumari , Chiranjeev Kumar

With the exponential proliferation of cloud services, the decision of trustworthy cloud service selection has become tremendously challenging nowadays. It demands an accurate decision system to carry out a comprehensive assessment of cloud services from various aspects. The immense complexity and limitations of existing approaches reduce the credibility of the service selection process; thus, further research is necessitated to produce more authentic service selection results. In this regard, this paper proposes a novel framework called Optimal Service Selection and Ranking of Cloud Computing Services (CCS-OSSR), which allows cloud customers to compare available service choices based on QoS (Quality of Criteria) criteria. The CCS-OSSR utilizes a hybrid multi-criteria decision making approach. Best worst method is used to rank and prioritize the QoS criteria and Technique for Order Preference by Similarity to Ideal Solution approach is employed to obtain the final rank of cloud services. To verify the applicability/effectiveness, the proposed methodology validated with the help of comprehensive analysis. In addition, we examine the proposed methodology in term of sensitivity analysis and comparative analysis. The outcomes of sensitivity and comparative analysis show that the proposed approach requires less pairwise comparisons and can provide better consistent solution against existing solutions.



中文翻译:

CCS-OSSR:基于混合MCDM的框架,用于优化服务选择和云计算服务排名

随着云服务呈指数级增长,如今,选择可信赖的云服务的决定已变得越来越具有挑战性。它需要一个准确的决策系统来从各个方面对云服务进行全面评估。现有方法的巨大复杂性和局限性降低了服务选择过程的可信度;因此,有必要进行进一步的研究以产生更真实的服务选择结果。在这方面,本文提出了一种称为“云计算服务的最佳服务选择和排名”(CCS-OSSR)的新颖框架,该框架允许云客户比较基于QoS(标准质量)标准的可用服务选择。CCS-OSSR利用混合多准则决策方法。使用最佳最差方法对QoS标准进行排序和优先级排序,并使用“与理想解决方案相似性”的“顺序首选项技术”获得云服务的最终排名。为了验证适用性/有效性,在综合分析的帮助下对所提出的方法进行了验证。此外,我们在敏感性分析和比较分析方面研究了所提出的方法。敏感性和比较分析的结果表明,所提出的方法需要较少的成对比较,并且可以针对现有解决方案提供更好的一致性解决方案。所提出的方法在综合分析的帮助下得到了验证。此外,我们在敏感性分析和比较分析方面研究了所提出的方法。敏感性和比较分析的结果表明,所提出的方法需要较少的成对比较,并且可以针对现有解决方案提供更好的一致性解决方案。所提出的方法论在综合分析的帮助下得到了验证。此外,我们在敏感性分析和比较分析方面研究了所提出的方法。敏感性和比较分析的结果表明,所提出的方法需要较少的成对比较,并且可以针对现有解决方案提供更好的一致性解决方案。

更新日期:2020-08-05
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