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Toward trustworthy cloud service selection: A time-aware approach using interval neutrosophic set

机译:迈向可信云服务选择:使用间隔中智集的时间感知方法

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Cloud services consumers face a critical challenge in selecting trustworthy services from abundant candidates, and facilitating these choices has become a critical issue in the uncertain cloud industry. This paper employs the time series analysis to address challenges resulting from fluctuating quality of service, flexible service pricing and complicated potential risks in order to propose a time-aware trustworthy service selection approach with tradeoffs between performance-costs and potential risks. The original evaluation data about the services is preprocessed using a cloud model, and interval neutrosophic set (INS) theory is utilized to describe and measure the performance-costs and potential risks of services. In order to calculate and compare the candidate services while supporting tradeoffs between performance-costs and potential risks in different time periods, we established a cloud service interval neutrosophic set (C1NS) and designed its operators and calculation rules, with theoretical proofs provided. The problem of time-aware trustworthy service selection is formulated as a multi-criterion decision-making (MCDM) problem of creating a ranked services list using C1NS, and it is solved by developing a CINS ranking method. Finally, experiments based on a real-world dataset illustrate the practicality and effectiveness of the proposed approach.
机译:云服务消费者在从丰富的候选人中选择可信赖的服务时面临着严峻的挑战,而在不确定的云产业中,促进这些选择已成为一个关键问题。本文采用时间序列分析来应对服务质量波动,灵活的服务定价和复杂的潜在风险所带来的挑战,从而提出一种在性能成本和潜在风险之间进行权衡的,可感知时间的可信赖服务选择方法。使用云模型预处理有关服务的原始评估数据,并使用间隔中智集(INS)理论来描述和衡量服务的性能成本和潜在风险。为了计算和比较候选服务,同时支持在不同时间段内性能成本和潜在风险之间的权衡,我们建立了云服务间隔中智集(C1NS),并设计了它的运算符和计算规则,并提供了理论证明。将时间感知的可信服务选择问题表述为使用C1NS创建排名服务列表的多准则决策(MCDM)问题,并通过开发CINS排名方法来解决。最后,基于真实世界数据集的实验说明了该方法的实用性和有效性。

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