AN ENERGY EEFICIENT VM ALLOCATION USING GENETIC ALGORITHM

Abstract

Cloud computing depicts a real paradigm nature and is deployed in the way systems should be. With the popularization of the internet, cloud computing systems came into evolution. In Cloud computing technology, Energy efficiency is becoming important due to increase in power consumption and carbon emission. In this paper, Modified Best Fit Decreasing (MFBD) algorithm is used which allocates VM on the basis of CPU utilization and we focus to improve the existing algorithm by applying novel optimization technique, a genetic algorithm for VM migration. The behavior is based on natural phases and its function adapts very well in virtualization. We used MATLAB for simulations and the parameters like Power consumption, VM migrations, and SLA violations are performed by comparing with the existing parameters. The experimental result shows better improvement in both VMs placement and migration and the ability to achieve significant energy savings when compared to the existing algorithm.