MCDM-Based Parametric Selection of Cloud Deployment Models for an Academic Organization

In the present scenario, academic organizations are looking toward the adoption of the cloud computing services to make improvements in teaching, learning, and research. Various cloud deployment models have been developed in past for effective implementation of the cloud computing. Due to such diversity of deployment models, the selection of these models becomes a very difficult task for the academic organizations. Further, this selection decision is dependent on various conflicting decision parameters. Therefore, the problem of cloud deployment model selection can be molded as a multi-criteria decision making (MCDM) problem. In this research article, a decision-making framework using Fuzzy-euclidean-Taxicab distance-based approach (Fuzzy-ETDBA) is developed and presented to solve the cloud deployment model selection problem. To demonstrate the presented framework, a case study is represented that involves the evaluation and selection of four cloud deployment models over three decision parameters consisting of seventeen sub-parameters. The selection results obtained depict that the public cloud deployment model is most preferable for the presented case study.