Enhancing Cloud Computing Performance Through Adaptive Load Balancing: an Enhanced PSO Algorithm and VM Load Balancer Approach

Document Type : Primary Research paper

Authors

1 Scholar, Department of Computer Engineering, Jagadambha College of Engineering & Technology, Yavatmal

2 Assistant Professor Department of Computer Engineering, Jagadambha College of Engineering & Technology, Yavatmal

Abstract

Cloud computing has revolutionized the way computational resources are utilized, offering scalability, flexibility, and cost-effectiveness. However, optimizing performance remains a challenge, particularly in managing dynamic workloads and resource allocation. This research presents a novel approach to enhance cloud computing performance through adaptive load balancing. By integrating an enhanced Particle Swarm Optimization (PSO) algorithm with a Virtual Machine (VM) load balancer, this study proposes a robust solution to efficiently allocate resources and balance workloads in cloud environments. The methodology is evaluated using simulations, demonstrating significant improvements in performance metrics such as response time, throughput, and resource utilization. The findings suggest that the proposed approach offers a promising solution for optimizing cloud computing performance in dynamic and heterogeneous environments.

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