CCS-OSSR: A framework based on Hybrid MCDM for Optimal Service Selection and Ranking of Cloud Computing Services

With the exponential proliferation of cloud services, the decision of trustworthy cloud service selection has become tremendously challenging nowadays. It demands an accurate decision system to carry out a comprehensive assessment of cloud services from various aspects. The immense complexity and limitations of existing approaches reduce the credibility of the service selection process; thus, further research is necessitated to produce more authentic service selection results. In this regard, this paper proposes a novel framework called Optimal Service Selection and Ranking of Cloud Computing Services (CCS-OSSR), which allows cloud customers to compare available service choices based on QoS (Quality of Criteria) criteria. The CCS-OSSR utilizes a hybrid multi-criteria decision making approach. Best worst method is used to rank and prioritize the QoS criteria and Technique for Order Preference by Similarity to Ideal Solution approach is employed to obtain the final rank of cloud services. To verify the applicability/effectiveness, the proposed methodology validated with the help of comprehensive analysis. In addition, we examine the proposed methodology in term of sensitivity analysis and comparative analysis. The outcomes of sensitivity and comparative analysis show that the proposed approach requires less pairwise comparisons and can provide better consistent solution against existing solutions.