Hybrid Approach for Virtual Machine Optimization using BAT Algorithm in cloud

The virtual machine (VM) in cloud is overutilized if it takes the total execution time of workflow more than the maximum acceptable limit. In this paper, bat Algorithm is hybridized with heuristic techniques to identify the VMs under overload condition and to optimize their utilization. In proposed model, the bat algorithm parameters (Frequency, velocity, loudness, pulse rate) are seeded by the heuristic approaches (HEFT and PEFT) to optimize makespan and cost of executing the workflows. The model is implemented in CloudSim and results are analyzed with reference to state-of-the-art ACO and PSO metaheuristics.