A PSO-Based Hierarchical Resource Scheduling Strategy on Cloud Computing

Abstract

Cloud computing environments facilitate applications by providing virtualized resources that can be provisioned dynamically. Computing resources are delivered by Virtual Machines (VMs). In such a scenario, resource scheduling algorithms play an important role where the aim is to schedule applications effectively so as to reduce the turn-around time and improve resource utilization. In this paper, we present a Particle Swarm Optimization (PSO) based strategy schedules applications to cloud resource taking into account both transmission cost and current load. In addition, a novel inertia weight was introduced in order to get the global search and local search effectively and avoid plunging into the local optimum. Finally, we experiment with application workflows by varying its performance and convergence analysis. © Springer-Verlag Berlin Heidelberg 2013.