Hybrid optimization algorithm for task scheduling and virtual machine allocation in cloud computing

Abstract

In the Internet era, cloud computing is evolved as the efficient distributed platform in the recent years. But the major issue related to the cloud platform is task scheduling. Allocating the suitable VM to the tasks is a challenging task in cloud computing. Many algorithms are proposed to optimize the scheduling process in the cloud environment. The existing algorithms have their own drawbacks. This paper proposed the hybrid model which uses the hierarchical process to prioritize the task before submitting to the scheduler. The Bandwidth-aware divisible task (BAT) scheduling model is modified by adding the Bar system model to develop the hybrid optimization mechanism. The Minimum overload and minimum lease policy is employed for applying the pre-emption in the data center to reduce the overload of the virtual machine. The performance of the proposed hybrid model is evaluated using different parameters. The simulation results prove the efficiency of the hybrid model.