Abstract
Job scheduling of scientific workflow applications in IaaS cloud is a challenging task. Optimal resource mapping of jobs to virtual machines is calculated considering schedule constraints such as timeline and cost. Determining the required number of virtual machines to execute the jobs is key in finding the optimal schedule makespan with minimal cost. In this paper, VMPROV algorithm has been proposed to find the required virtual machines. Priority-based round robin (PBRR) algorithm is proposed for finding the job to resource mapping with minimal makespan and cost. Executions of four real-world scientific application jobs by PBRR algorithm are compared with MINMIN, MAXMIN, MCT, and round robin algorithms execution times. The results show that the proposed algorithm PBRR can predict the mapping of tasks to virtual machines in better way compared to the other classic algorithms.
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