Energy-aware Virtual Machine Selection and Allocation Strategies in Cloud Data Centers

These days, information technologies are expanding exponentially so the need for high-speed processors and huge storage space are developing quickly. As a result of increasing requests, more resources are required to satisfy the client's necessities. Thus, in a cloud environment, the large number of resources consumes a lot of energy during their operation, which is turned into a key issue nowadays and demands a critical discussion in the present scenario. This research paper investigates and explores the literature on the assignment of virtual machines to hosts in a data center according to variable workload requests of different cloud consumers application executing on the virtual machines. The choice of ideal virtual machines and their placement on host prompts to limit the energy utilization. This paper proposes an algorithm for improving virtual machine selection and allocation strategies in cloud data centers. The proposed algorithm is then compared with existing algorithms on the basis of performance metrics like energy consumption and VM migrations using different threshold values. As a result, the proposed algorithm emerged to be the optimized one in enhancing the use of cloud resources by lessening the energy utilization of datacenter.