A Novel Parallel Jobs Scheduling Algorithm in The Cloud Computing

Abstract

Cloud Computing is a computational model that provides all computing services and its requirements over the Internet. So our computation is always available without burdens of carrying large-scale hardware and software. The utilization of resources has been decreasing due to the growth of parallel processing in most parallel applications. Accordingly, job scheduling, one of the fundamental issues in cloud computing, should manage more efficiently. The accuracy of parallel job scheduling is greatly important for cloud providers in order to guarantee the quality of their service. Given that optimal scheduling improves utilization of resources, reduces response time and satisfies user requirements. Most of the current parallel job scheduling algorithms do not use the consolidation of parallel workloads to improve scheduling performance. This paper introduces a scheduling algorithm enriches the powerful ACFCFS algorithm. To begin with, we employ tentative runs, workload consolidation and two-tier virtual machines architecture. Particularly, we consider deadline for jobs in order to prevent starvation of parallel jobs and improve performance. The simulation results indicate that our algorithm considerably reduces the makespan and the maximum waiting time. Therefore it improves scheduling compare to the basic algorithm (ACFCFS). Overall, it can be employed as a strong and effective method for scheduling parallel jobs in the cloud.