Developing a Cloud Computing Data Center Virtual Machine Consolidation Based on Multi-objective Hybrid Fruit-fly Cuckoo Search Algorithm

Abstract

The virtual machine (VM) placement problem is a major issue in optimizing resource utilization of cloud data center. With rapid development of cloud computing, efficient algorithms are needed to reduce the power consumption and save energy in the cloud data center. Many researchers have investigated Meta heuristics algorithms to solve this problem based on the NP-Hard problem. In this paper, we consider a novel multi-objective Hybrid Fruit-fly Algorithm for virtual machine consideration in the cloud data center. The proposed algorithm is based on the works based on the VM Migration, which are mainly used to minimize over provisioning of physical machine by consolidating VMs on under-utilized physical machine (PM). The experimental results show that the proposed multi objective hybridized Fruitfly optimization technique which is based on the modified cuckoo search algorithm enhances the convergence rate and its optimization accuracy is comparable to other existing multi objective algorithms. The proposed algorithm results show that a significant reduction of unnecessary VM migration, avoids unstable host selection and also improves the application performance and efficiencies of power usage.