Enhancing cloud efficiency: an intelligent virtual machine selection and migration approach for VM consolidation

Abstract

Cloud-based computing, despite its numerous benefits, frequently exerts a negative influence on the environment. The primary concern lies in the emission of greenhouse gases and the consumption of electricity by cloud data centers, which demands considerable scrutiny. Virtual machine consolidation (VM) is a widely adopted strategy aimed at achieving energy efficiency and maximizing resource utilization. The consolidation of VMs is a fundamental process in the development of a sophisticated cloud resource management system that prioritizes energy efficiency. The underlying premise is that by shifting VMs onto a reduced number of physical machines, it is possible to achieve optimization objectives, increase the utilization of cloud servers, and concurrently decrease energy consumption in cloud data centers. This proposed solution utilizes the best fit decrease (BFD) approach for VM allocation. An enhanced Greedy selection approach is proposed for VM migration, utilizing the Genetic method optimization method.