Hybrid Particle Swarm Optimization scheduling for cloud computing

Abstract

Cloud computing is revolutionizing on how information technology is used by organizations and individuals. Cloud computing provides dynamic services with virtualized resources over the Internet. It ensures facilities to develop, deploy, and manage applications `on the cloud' for end users entailing resources virtualization that maintains and manages itself. Scheduling is a task performed to get maximum profit to increase cloud computing work load efficiency. Its objective is using resources properly and managing load between resources with minimum execution time. High communication cost incurs in clouds prevent task schedulers from being applied in a large scale distributed environment. This study proposes a hybrid Particle Swarm Optimization (PSO) which performs better in execution ratio and average schedule length.