Improve Workflow Scheduling Technique for Novel Particle Swarm Optimization in Cloud Environment

Cloud computing is the latest distributed computing paradigm [1], [2] and it offers tremendous opportunities to solve large-scale scientific problems. However, it presents various challenges that need to be addressed in order to be efficiently utilized for workflow applications. Although the workflow scheduling problem has been widely studied, there are very few initiatives tailored for cloud environments. Furthermore, the existing works fail to either meet the user’s quality of service (QoS) requirements or to incorporate some basic principles of cloud computing such as the elasticity and heterogeneity of the computing resources. In this paper proposes a resource provisioning and scheduling strategy for scientific workflows on Infrastructure as a Service (IaaS) clouds. The proposed system presents an algorithm based on the particle swarm optimization (PSO), which aims to minimize the overall workflow execution cost while meeting deadline constraints. Keywords—Cloud Environments, resource allocation, scheduling, PSO, Multi Cloud Provider