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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >A Heterogeneous QoS-Based Cloud Service Selection Approach Using Entropy Weight and GRA-ELECTRE III
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A Heterogeneous QoS-Based Cloud Service Selection Approach Using Entropy Weight and GRA-ELECTRE III

机译:基于异质QoS的云维修选择方法,使用熵权和GRA-Extenti III

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摘要

With the development of cloud computing, more and more resources are provided in the form of cloud services. Then how to select suitable cloud service for users without professional knowledge has become an important issue. Existing cloud service selection models are usually considered as QoS-aware evaluation focused models. In practice, the QoS attributes have problems like subjectivity, vagueness, and uncertainty, and a range of formats are involved to describe QoS attributes. Therefore, it is necessary to consider the heterogeneous formats of QoS attributes in cloud service selection process. The aim of this paper is to develop a novel cloud service selection approach using entropy weight and GRA-ELECTRE III that can handle heterogeneous QoS attributes simultaneously. In the proposed approach, heterogeneous QoS attributes are handled simultaneously by being transformed into intuitionistic fuzzy numbers; the relative weights of QoS attributes are calculated objectively by the extended entropy measure method under intuitionistic fuzzy environment; and cloud services are evaluated by GRA-ELECTRE III integrated method under intuitionistic fuzzy environment. Experimental results show that the proposed approach has good stability and discrimination in dealing with heterogeneous data and can effectively avoid compensation between attributes.
机译:随着云计算的发展,越来越多的资源以云服务的形式提供。然后如何为没有专业知识的用户选择合适的云服务已成为一个重要问题。现有的云服务选择模型通常被视为QoS感知评估聚焦模型。在实践中,QoS属性具有主观性,模糊性和不确定性等问题,并且涉及描述QoS属性的一系列格式。因此,有必要考虑云服务选择过程中QoS属性的异构格式。本文的目的是使用熵权和GRA-Electre III开发一种新颖的云服务选择方法,可以同时处理异构QoS属性。在所提出的方法中,通过转换为直觉模糊数来同时处理异构QoS属性;通过直觉模糊环境下的扩展熵测量方法,客观地计算QoS属性的相对权重;通过直觉模糊环境下GRA-Electre III集成方法评估云服务。实验结果表明,该方法在处理异构数据方面具有良好的稳定性和歧视,可以有效地避免属性之间的补偿。

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