An Energy-Efficient Virtual Machine Scheduling Algorithm in Cloud Data Center

Power consumption has a significant influence on resource allocation, which has a negative effect on the environment. To lessen the negative effects, an effective resource allocation algorithm is needed. In this paper, we suggested a unique hybrid approach for energy-efficient scheduling of virtual machines (VMs) in cloud data centers called Energy Efficient Particle Swarm Optimization (EE-PSO), which combines Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). This integration is special since it makes use of both algorithms’ advantages to improve scheduling effectiveness and energy consumption. The novelty lies in how GA and PSO are combined, which differs from previous attempts where these algorithms were either used separately or in a less integrated manner. EE-PSO represents significant achievement toward achieving the goals of decreasing power usage and promoting green computing practices.