Optimized VM Migration for Energy and Cost Reduction Using TSO Algorithm in Cloud Computing

Virtual machines (VMs) in cloud computing can be transferred from one physical host to another via VM migration. The placement and migration of virtual machines are a multi-objective optimization problem. An effective VM allocation policy will reduce hotspots, improve QoS preservation, and increase energy efficiency. Additionally, it will lower the data centre’s operating expenses. In this paper, optimized VM migration using Tuna Swarm Optimization (TSO) Algorithm OVM-TSO is proposed for energy and cost reduction in cloud computing. The overloaded and underloaded VMs from any host are selected for migration. For selecting the target VMs for placement, separate fitness function is derived for overloaded and underloaded hosts. Then TSO algorithm is applied for target VM selection for the migrated VMs such that the overall energy consumption, resource wastage, and migration cost are reduced. Simulation results using CloudSim show that the proposed OVM-TSO algorithm minimizes the power consumption, reduces the response delay, and increases the CPU utilization, during migrations.