Hybrid Metaheuristic Approach for Optimal Load Balancing in Heterogeneous Cloud Environments Using PSO and WOA

Cloud computing has transformed the delivery of computational services. However, load balancing in heterogeneous cloud environments remains a complex challenge due to dynamic resource availability and fluctuating workloads. This paper presents a novel hybrid metaheuristic algorithm combining Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA) to achieve optimal load distribution. The proposed hybrid method harnesses the exploration ability of PSO and the exploitation strengths of WOA. Experimental results show significant improvements in task execution time, load uniformity, and overall system throughput compared to using PSO or WOA independently.