Cloud Service ranking and Selection using Linear Programming

Abstract

Cloud computing is basically an internet based computing, whereby shared configurable resources are provided to cloud service consumers as services on demand. As an increasing growth of cloud computing, many enterprises provide different cloud services to cloud service consumers. From cloud service consumer's perspective, it is difficult to choose an appropriate cloud service that satisfies their QoS requirements. As requirements of one cloud service consumer will vary from another, dynamic ranking has to be used to satisfy the requirements of different cloud service consumers. A simple model is needed to address the dynamic ranking of cloud services. The dynamic ranking and selection of cloud services is solved using Linear Programming(LP) model. This project considers quantifiable attributes such as processor speed, cost, etc. and some non-quantifiable attributes to rank various cloud services according to the requirements of cloud service consumer using Linear Programming(LP) technique.

Parameter Reputation Model for Cloud Service Recommendation and Ranking Using Opinion Mining

“…CloudEval applies a notable multi-attribute decision-making technique, namely a Grey Relational Analysis for the selection process. Preethi et al [16] proposed a dynamic ranking and selection of cloud services using linear programming. It considers both quantifiable and non-quantifiable QoS parameters to provide an appropriate service that fulfils the greater part of the requirements of cloud service consumers using Linear Programming.…”