An energy-aware migration framework using metaheuristic algorithm in cloud computing

Pervasive computing requires dynamic, energy-efficient cloud architecture to deploy services in VMs to distributed computing nodes. This mapping must ensure the service level agreement (SLA) runs VMs without disruption. This paper presents an energy-efficient metaheuristic Rock Hyrax algorithm-based cloud VM migration architecture. The male Rock Hyraxes find food and ensure the colony’s safety. His behavior has been mimicked in our proposed algorithm for finding energy-efficient compute nodes. A multi-objective VM migration function considers job submission deadlines. The proposed method reduces SLA violations and energy utilization while optimizing resource utilization. When evaluating the project, makespan, energy efficiency, and SLA violations were considered. The proposed algorithm is simulated on the CloudSim simulator considering both resources and jobs dynamic in nature. The suggested strategy outperforms ant colony optimization, particle swarm optimization, cuckoo optimization, and modified gray wolf optimization. The migration technique improves resource utilization by 18%, makespan time by 5%, SLA violation by 13%, and energy usage by 15%.