Hybrid Genetic Swarm Scheduling for Cloud Computing

Abstract

Cloud computing ensures access to shared resources and common infrastructure offering services on demand over a network for operations to meet changing business needs Scheduling is a prominent activity that is executed in a cloud computing environment To increase cloud computing work load efficiency tasks scheduling is performed to get maximum profit In cloud high communication cost prevents task schedulers from being applied in large scale distributed environments Cloud environment system scheduling is NP-complete To solve the NP complete and NP hard problems heuristic approaches are used This study proposes a hybrid optimization based on Particle Swarm Optimization PSO and Genetic Algorithm GA for scheduling in cloud environments