A Recommendation System for Cloud Services Selection based on Intelligent Agents

Objectives: To provide a recommendation system for cloud services selection based on intelligent agents. Methods/ Statistical Analysis: There have been many assortments of research, frameworks, and systems that discussed in many kinds of literature for selection of most advantageous service to fulfill the requirements of consumers. QoS parameters in addition to cloud service related QoS parameters have been used, but an agent-based cloud computing system has been introduced now that facilitate the CSS for better usage and service for the consumer. In this study, we proposed a service selector system on computer trust merit of the cloud purveyor. In previous studies, the authors had used the QoS model to solve the problem of cloud service vendor selection in multidimensional technique but this was not practically approachable. But we implement the multi-agent system (MAS) approach where one agent is liable to intermingle with the client for unambiguous service. MAS have very supple and self-directed nature, due to this quality MAS is the very authentic approach for users. Findings: In this proposal a selection and recommendation methodology implemented using multi-agents paradigm, has been proposed that recommends the most aspirant service from similar grouped services. The experimental output confirms that the proposed methodology can effectively select an optimal required service for end users. Cloud computing system with the help of multi-agents offer better agent-based intelligent cloud solutions for complex computational tasks. Application/Improvements: Multi-agents can be employed as key components for the selection and recommendation of intelligent cloud applications, making cloud infrastructure more autonomous, adaptive, and flexible in resources management, services provisioning and in running large-scale applications.