A Hybrid Evaluation Framework for QoS Based Service Selection and Ranking in Cloud Environment

With the growing demand and the varied availability of a large number of cloud services, it has become difficult to discover a relevant cloud service that can satisfy cloud customer's functional needs. From the customer's point of view, it is hard to decide, which cloud service satisfy their QoS (Quality of Service) requirement and what is the basis for their selection. To assist the cloud customer in the optimal service selection, a framework has been proposed, which allows cloud customer to assess the many cloud service providers by considering the QoS attribute value. In this work, we put forward an improved MCDM (Multi Criteria Decision Making) methodology that improves the existing cloud service selection methods. In particular, we use Best-Worst method for calculating the attribute weights and apply TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method for calculating the final rank of cloud service provider. Furthermore, we use a real time case study to analyze the pertinence of the proposed technique. The experimental results affirm the feasibility and effectiveness of the proposed methodology. This research helps to create a strong competition among the cloud service providers.