An Efficient Hybrid Ranking Method for Cloud Computing Services Based On User Requirements

Abstract

An increase in the number of cloud services makes service selection a challenging issue for cloud users. It is important to determine the best service that can fulfill user requirements. To this end, this paper proposes a hybrid multiple-attribute decision-making (MADM) model. The proposed method considers service measurement index cloud (SMICloud) structure for qualitative attributes of cloud services as well as user requirements based on fuzzy values to consider vague user requirements. Analytical hierarchy process (AHP) and fuzzy logic are used to rank cloud services. Furthermore, a fuzzy Delphi filtering method is proposed to decrease the execution time of ranking cloud services. In experiments, different aspects such as accuracy, execution time, scalability, and sensitivity analysis are investigated. The results confirm that the proposed method outperforms available methods in terms of execution time and scalability. Furthermore, the experiments show that the proposed method has achieved an accuracy of 96%.