Energy-aware VM consolidation approach using combination of heuristics and migration control

Cloud based services are getting more and more eminent as they offer Pay-as-you-go service model. Increased need of computing and reliability are other factors of cloud based datacenters to be grown in number. However, energy consumption by Cloud based Datacenters draw negative attention as they consume considerable amount of energy while in operation. Researchers have proposed various techniques to improve the power consumption scenario of virtualized datacenters. Energy-aware dynamic Virtual Machine consolidation is one of the techniques where utilization of datacenters are monitored and underutilized datacenters are shutdown by migrating VM to other capable datacenters. In this research, we are proposing a new virtual machine consolidation algorithm by doing amalgamation of heuristic approach & migration control and compare it to other heuristic methods which are already proposed in literature. We have used Cloudsim toolkit to simulate our experiment and to evaluate the performance of the proposed algorithm, we have used real-world work load traces of Planet lab VMs. From the comparison with existing energy aware VM consolidation methods, it is found that performance of our algorithm is better than other proposed heuristic approaches.