Efficient Dynamic Load Balancing in Cloud Computing Utilizing Biruni Earth Radius Optimization Algorithm

Cloud Computing (CC) is a widely used technology that provides virtualized computer resources over the internet. The performance of these cloud systems is primarily influenced by several factors, including load balancing. Load balancing is the process of distributing dynamic workloads across cloud systems and ensuring that resources are allocated equally, preventing database servers from becoming overcrowded or underutilized. This paper proposes an Efficient Dynamic load-balancing approach in CC using Biruni Earth Radius Optimization Algorithm combined with an Adaptive and Collaborative Optimization technique (BEROA-ACC-OLB). Initially, the Biruni Earth Radius Optimization Algorithm (BEROA) is employed to significantly improve load balancing. The performance of the BEROA-ACC-OLB is evaluated under metrics such as energy utilization, makespan, number of tasks migrated, time required, resource utilization, response time, standard deviation, and throughput. The results show that the proposed approach achieves 27.4%, 31.1%, 30.2% less energy utilization, 26.4%, 33.14%, and 32.24% higher makespan, and 29.43%, 34.13%, and 33.25% higher migration compared to the existing techniques: Types for Load Balancing in CC, the Mantaray Modified Multi-Objective Harris Hawk Optimization Approach, and Load Balancing in CC Environment utilizing Grey Wolf Optimization Algorithm depending on reliability.