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

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.