An improved round robin time sharing algorithm for optimizing data mapping in cloud computing environments

Abstract

Cloud computing in recent years has been widely applied in a wide number of applications and fields. However, allocating tasks to virtual machines (VMs) remains a part that needs enhancement. Task scheduling algorithms in heterogeneous computing system are required to satisfy high-performance data mapping requirements. The efficient allocation between resources and tasks decreases waiting time (WT), turnaround time (TT) and maximizes resource utilization. Various task scheduling algorithms, including round robin (RR) and some improved RR algorithm are used for cloud environment. A novel time-sharing algorithm (NRRTSA) is introduced, demonstrating enhancements in WT and TT. Simulation findings indicate that the NRRTSA algorithm effectively schedules multiple requests (cloudlets) among several VMs, the proposed NRRTSA outperforms RR and other algorithms in terms of the average of both TT and WT. The average turnaround time (ATT) is enhanced with a ratio of 10.8% to 45%, the average waiting time (AWT) is enhanced with a ratio of 10.9% to 45%.