A Multi-Objective Initial Virtual Machine Allocation in Clouds using Divided KD Tree

Recently increased demand in computational power resulted in establishing large-scale data centers. The developments in virtualization technology have resulted in increased resource utilization across data centers, but energy efficient resource usage becomes a challenge. It has been estimated that by 2015 infrastructure and energy costs would contribute about 75%, whereas IT would contribute just 25% to the overall cost of operating a data center. Various algorithms have been developed for optimizing the utilization of the resources but as the popularity of the cloud computing is increasing there is need to explore new idea to reduce the overall power consumption which leads to minimize overall operational cost. The paper focuses on a novel multi-objective approach which tries to minimize the virtual machine scheduling delay and active servers by switching off the remaining for energy efficient computing using a multidimensional data structure Divided KD Tree.