Enhancing Resource Utilization in Cloud Environments using the Whale Optimization Algorithm

Cloud computing provides many features to the user to retrieve, update and access the data virtually with the help of internet. It has emerged as a transformative pattern in information technology, giving scalable and on-demand access to a wide variety of resources. However, effective resource management continues to be a major obstacle to fully utilizing the advantages of cloud systems. This study examines the use of three different optimization algorithms, a Standard Particle swarm optimization (PSO), Aging Leader and Challenger (ALC)-PSO, and Whale Optimization Algorithm (WHO), to enhance resource allocation in cloud infrastructures. All these algorithms provide the greatest efficiency when we compare them to the 100 number of iterations to 1000 iterations. The Whale Optimization Algorithm (WOA) provides results highest in all among the standard PSO and the ALC-PSO makespan. This technique can be used in the context of cloud computing to dynamically assign resources depending on changes in workload and demand in real-time. This research aims to improve cloud resource utilisation by using swarm optimisation algorithms to the problem.