Workflow Scheduling In Clouds Using Randomized Scheduling Algorithm

Abstract

The provisioning of on-demand resources makes it optimal for executing scientific application workflows in cloud computing. An application starts the process with a small number of resources, and it allocates the resources when required. However, workflow scheduling belongs to NP-hard class of problems, so optimization techniques are preferred for the solution. This paper explores the effect of a Randomized scheduling algorithm in workflow scheduling for the scheduling problem. The use of Randomized scheduling algorithm in comparison with other scheduling algorithms increases the efficiency of workflow scheduling in various scientific workflows and simulators. The experimental result confirms that the Randomized scheduling algorithm well performed than other scheduling approaches and provides better scheduling with reduced makespan.