In the era of multi-cloud environments, the challenge for end users or organizations is to select the most appropriate cloud service provider (CSP) due to the complexity and variability of service-level offerings by various CSPs. In this paper, we propose a MAGIQ-TOPSIS-Fuzzy-logic based Cloud Service Provider Ranking (MTF-CSPR) model, which provides a more robust and intelligent decision-making system in CSP selection. The proposed model addresses both qualitative and quantitative evaluation criteria by capturing and processing the inherent vagueness of linguistic assessments through fuzzy logic. MAGIQ is employed to derive optimal weights for evaluation criteria that reflect their relative importance towards the alternatives. TOPSIS is applied to rank CSPs where the ideal and anti-ideal solutions are derived, and then based on CSP's proximity to the ideal solution, the ranks are derived. The proposed model ensures accuracy, scalability, and context-awareness for the CSP ranking by integrating subjective expert opinions with objective performance metrics. Experimental evaluation demonstrates that the proposed MTF-CSPR model provides more consistent and accurate rankings compared to conventional standalone approaches, as well as the other ranking models under consideration, providing better decision-support for enterprises to adopt the hybrid or multi-cloud strategies.
SARAF et al. (Thu,) studied this question.