Harmonic Migration Algorithm for Virtual Machine Migration and Switching Strategy in Cloud Computing

Abstract

Nowadays, cloud computing (CC) has been utilized broadly owing to the services it provides which can be received from any location at any time on the basis of the customer's requirements. A huge amount of data transmission is made from both user to host as well as host to the customer in the cloud environment, but here placing the virtual machine (VM) on a suitable host and data transferring is a challenging task. In this research, a harmonic migration algorithm (HMA) is developed by combining both the migration algorithm (MA) and the harmonic analysis (HA) for migrating a VM from an overloaded to an under-loaded physical machine (PM) and enabling or disabling the VM through switching strategies in CC. The tasks are allocated to the corresponding VM in a round-robin (RR) manner and subsequently, the load of the VM is predicted through the gated recurrent unit (GRU). The HMA technique migrates the VM when the predicted load is higher than the value of threshold and also, it enables or disables the VM when necessary. Thus, the performance of the developed HMA is improved over the other previous schemes at tasks 100, 200, 300, and 400 by varying the iterations. Therefore, the predicted load, makespan, and resource utilization of the developed HMA are 0.148, 0.327 s, and 0.482% for task 100 at iteration 100.