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首页> 外文期刊>Journal of supercomputing >A comparative analysis of prominently used MCDM methods in cloud environment
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A comparative analysis of prominently used MCDM methods in cloud environment

机译：云环境中占据MCDM方法的比较分析

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摘要

Incloud computing, the selection of an efficient multi-criteria decision-making (MCDM) method (with minimum time complexity and maximum robustness) is a challenging and interesting problem. The time complexity and robustness of a MCDM method depend upon the methodology of evaluating the best alternative (i.e., cloud service). Although numerous MCDM methods are proposed for the quality-of-service based service selection in the cloud, still the issue of selecting the most efficient method remains unresolved. This paper presents a comparative analysis of the prominently used MCDM methods in terms of time complexity and robustness. The MCDM methods are used in the geographical region selection problem for Amazon Web Service cloud, and a comparative analysis of the obtained ranking results is performed. Further, application-specific analysis and sensitivity analysis are performed to ascertain the robustness of ranking methods. Experimental analysis is performed on the large-scale synthetic dataset to get the ranking overhead, i.e., time complexity of different MCDM methods.
机译：随附计算，选择有效的多标准决策（MCDM）方法（最小时间复杂度和最大鲁棒性）是一个具有挑战性和有趣的问题。 MCDM方法的时间复杂性和鲁棒性取决于评估最佳替代方案（即云服务）的方法。虽然提出了许多MCDM方法用于云中基于服务质量的服务选择，但仍然选择最有效的方法的问题仍未解决。本文提出了在时间复杂性和鲁棒性方面的突出使用的MCDM方法的比较分析。 MCDM方法用于亚马逊Web服务云的地理区域选择问题，并进行对等级结果的比较分析。此外，执行特定于应用的分析和灵敏度分析以确定排名方法的鲁棒性。在大规模合成数据集上执行实验分析，以获得排名开销，即不同MCDM方法的时间复杂性。

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