An Optimization based Virtual Machine Migration Algorithm for Cloud Computing

Abstract

Cloud computing data centers host thousands and thousands of virtual machines (VMs) in real life circumstances. Using the growth of cloud computing, computing resources are provisioned as metered on-demand services through networks, and certainly will be instantly released and allocated with just minimal management work. The virtual machine is one of the most commonly used resource carriers in which business services are encapsulated in the cloud computing paradigm.  Energy usage of massive-scale cloud data centers is raising unacceptably. There clearly was a necessity to boost the vitality efficiency of these data centers Server that is using Consolidation is aimed at minimizing the sheer number of Active Physical Machines (APMs) in a data center. Excellent VM migration and placement methods work as a vital to consolidation that is optimum. A number of the recently proposed techniques understand dynamic consolidation while enhancing the VM placement. This paper provides a VM that is new Migration with VM Aggregation and Genetic algorithm (VMA-GA). This VMA-GA solves the difficulty of allocation between VMs which to be migrated and hosts that are underutilized. In VMA-GA, a novel coding that is genetic predicated on VM aggregation algorithm is proposed.