A resource aware VM placement strategy in cloud data centers based on crow search algorithm

Virtual machine (VM) placement in cloud data centers is a challenging task. With the increasing popularity of cloud computing across the globe, a large number of VMs are to be consolidated on a minimum number of data centers (DCs) to optimize the energy consumption and data center utilization. In this paper, we propose a resource aware approach based on a metaheuristic crow search algorithm (CSA) to consolidate a large number of VMs on minimal DCs to meet the Service level agreement (SLA) and desired quality of service (QoS) with maximum data center utilization. We propose two independent techniques, (i) greedy crow search (GCS), (ii) travelling salesman problem based hybrid crow search (TSPCS), to meet the desired objectives. A comparative study has been made from the obtained results. To evaluate the performance of proposed methods we compare them with the classical First Fit (FF) approach and the proposed methods significantly outperform the classical method.