CBWO: a novel multi-objective load balancing technique for cloud computing

Abstract

In cloud computing systems, the growing demand for diverse applications has led to challenges in resource allocation and workload distribution, resulting in increased energy consumption and computational costs. To address these challenges, we propose a novel load-balancing method, namely CBWO, that integrates Chaos theory with the Black Widow Optimization algorithm. Our approach is designed to optimize cloud computing environments by improving energy efficiency and resource utilization. We employ CloudSim for simulations, evaluating key performance metrics such as energy consumption, resource utilization, makespan, task completion time, and imbalance degree. The experimental results demonstrate the superiority of our method, achieving average improvements of 67.28% in makespan and 29.03% in energy consumption compared to existing solutions.