A Heterogeneous QoS-Based Cloud Service Selection Approach Using Entropy Weight and GRA-ELECTRE III

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.