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Cloud-FuSeR: Fuzzy ontology and MCDM based cloud service selection

机译:Cloud-FuSeR:基于模糊本体和基于MCDM的云服务选择

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摘要

With the rapidly growing number of available Cloud services, to fulfill the need for ordinary users to select accurate services has become a significant challenge. However, as a Cloud service environment encompasses many uncertainties that may hinder users to make sound decisions, it is highly desirable to handle fuzzy information when choosing a suitable service in an uncertain environment. In this paper, we present a novel fuzzy decision-making framework that improves the existing Cloud service selection techniques. In particular, we build a fuzzy ontology to model uncertain relationships between objects in databases for service matching, and present a novel analytic hierarchy process approach to calculate the semantic similarity between concepts. We also present a multi-criteria decision-making technique to rank Cloud services. Furthermore, we conduct extensive experiments to evaluate the performance of the fuzzy ontology-based similarity matching. The experimental results show the efficiency of the proposed method.
机译:随着可用云服务数量的迅速增长,满足普通用户选择准确服务的需求已成为一项重大挑战。但是,由于云服务环境包含许多不确定性,可能会阻碍用户做出正确的决定,因此在不确定环境中选择合适的服务时,非常需要处理模糊信息。在本文中,我们提出了一种新颖的模糊决策框架,该框架改进了现有的云服务选择技术。特别是,我们建立了一个模糊本体来对服务匹配数据库中对象之间的不确定关系建模,并提出了一种新颖的层次分析法来计算概念之间的语义相似度。我们还提出了一种多标准决策技术来对云服务进行排名。此外,我们进行了广泛的实验,以评估基于模糊本体的相似度匹配的性能。实验结果表明了该方法的有效性。

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