Intelligent Cloud Service Selection Using Agents

Abstract

One of the most recent developments within computer science is cloud computing which provides services (power, storage, platform, infrastructure etc.). Many clouds provide services are based on cost, efficiency, performance, and quality. Stakeholders have to compromise cost sometimes and performance or quality other times. Provision of the best quality based services to its stakeholders and to impart intelligence, agents can play important roles especially by learning the structure of the clouds. Agents can be trained to observe differences and behave intelligently for service selection. To rank different clouds, we propose a new technique performance factor for the provision of services based on intelligence. The research objective is to enable cloud users in selecting cloud service according to their own requirements. The technique assigns performance factor for each service provided by cloud and ranks it as whole. By doing so, quality of the services can be highly improved. We validate our approach with a case study, which emphasizes the need to rank cloud services of widely spreading and complex domains.