Efficient Power Management using Fuzzy Logic for Cloud Computing Environment

Abstract

In recent years, consumption of energy in the data center has acquired huge significance because of the huge consumption leading to secondary issues. To reduce the energy consumption in the data center, the dynamic VM consolidation is found to be the best technique. VM selection is important in the dynamic VM consolidation technique. The main objective towards VM consolidation is to select the VM from overloaded host and move towards undersubscribed host in the cloud data center. Fuzzy markov algorithm will improve the energy in the cloud data center. Various attributes with Fuzzy logic has been categorised in the dynamic VM consolidation. The proposed VM selection model is evaluated by considering the VM instances with homogeneous and heterogeneous hosts. The VM consolidation has been tested with the real data center data set. To check the performance in energy consumption, SLA violation, time consumption of the working host and performance degradation due to migration is considered. Cloudsim toolkit is used to check with the simulation results. The experimental results show the VM selection model is capable of improving the energy efficiency in the cloud data center up to 5.57 %, 4.89 % and 4.36 % compared to existing VM selection Minimum Migration Time, Constant First Selection and Maximum Correlation methods.