Cloud Service Provider Selection Using Fuzzy Data Envelopment Analysis Based on SMI Attributes

Abstract

A variety of business firms are moving towards the cloud after realizing the benefits and success of using cloud technology. With multiple cloud service providers having different features, selecting the best or ranking them becomes a tedious task. There are several multi-criteria decision-making models (MCDM) trying to handle the selection of the best cloud service provider problem. A significant amount of research focused on MCDM models using quality of service (QoS) characteristics, but not much research has been conducted to address the fuzziness inherent in data. Therefore, a suitable model for choosing suitable cloud service providers is proposed in this work to address this data fuzziness. The SMI attributes recommended by CSMIC, approved by ISO, are considered as the evaluation criteria for the evaluation of cloud service providers. In this research work, fuzzy DEA is used to compute the efficiency values of cloud service providers and modified Chen and Klein method is used to arrive at the final ranking of cloud service providers(CSPs).