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.