Enhanced Fuzzy AHP-TOPSIS for Cloud Service Selection

Choosing the right cloud service provider and cloud services according to cloud user requirements is a complex task, due to the increase in the number of cloud providers. Multi-criteria decision making (MCDM) is used where selecting, comparing and ranking of different Criteria of multiple alternatives is a requirement. Cloud providers present all kinds of cloud services, but they vary in quality, costs, customer experience, and service delivery. One of the problems with current cloud computing is the commitment of cloud service providers to the Service Level Agreement (SLA) with cloud providers users, but there are little verification frameworks to verify that cloud service providers provide cloud services according to their commitment. In the current literature, there is a lack of assessment models that provide the true status of cloud providers to cloud users. Therefore, this paper focuses on designing a new technique for selecting cloud service in the fuzzy environment by relying on Fuzzy AHP-TOPSIS by integrating the fuzzy analytical hierarchy process (AHP) concepts and the ideal solution (TOPSIS) concepts. The structure of the cloud service selection problem and the weights of the standards are determined by The Fuzzy AHP technique concepts. Fuzzy TOPSIS concepts used to arrange the final solution. The effectiveness and efficiency of the proposed technique is clarified by increasing accuracy by almost 15% through implementation and case studies.