A Critical Analysis of Energy Efficient Virtual Machine Placement Techniques and its Optimization in a Cloud Computing Environment

Abstract

Infrastructure-as-a-service cloud computing providers with on-demand infrastructures have become a promising alternative to the rising cost of ownership for computing infrastructures in many enterprises. Many of the touted gains in the cloud model come from resource multiplexing through virtualization technology that allows cloud-scale datacenters to improve resource utilization and energy efficiency. This paper provides a critical analysis on the basis of literature review of the state-of-the-art research on energy efficient dynamic allocation of virtual machines to hosts in a datacenter as per variable workload demands of different application running on the virtual machines and literature review suggests that further optimization of the virtual machine placement can be done using live migration. So, this paper proposes a technique for optimizing virtual machine placement by live migration using dynamic threshold values ensuring a deadlock free resource allocation focusing on multidimensional resources. The goal is to improve the overall utilization of computing resources thus reducing the energy consumption of datacenter.