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Published Subscription Review Article
Comparative Analysis of Classical, Metaheuristic, and Reinforcement Learning Approaches to Load Balancing in Cloud ComputingBy Mahesh Loya, Punam Shinde
Abstract: Efficient load balancing remains one of the most critical challenges in cloud computing, particularly as modern cloud environments rely on heterogeneous virtual machines (VMs) with varying computational capabilities. The effective distribution of workloads across these resources directly influences system performance, energy efficiency, and service reliability. This paper presents a comparative evaluation of three major categories of load-balancing approaches: traditional scheduling heuristics, nature-inspired metaheuristic algorithms, and reinforcement learning (RL)-based techniques. The …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 2, 2026 · pp. 1–6 Read article →