Load balancing is an important component in cloud computing that ensures of optimal resource
distribution, improved system performance, and high availability. As cloud environments
experience fluctuating user demands and dynamic workloads, effective load balancing techniques
become essential to maintaining environment’s scalability, reliability, and energy efficiency. This
paper presents a comparative study of load balancing algorithms- static, dynamic, and hybrid.
Forty-Nine research papers focused on load balancing are collected from various resources
systematically analyzed and evaluated these algorithms based on key parameters- Load
Distribution, Resource Allocation Efficiency, Adaptability, Scalability, Fault Tolerance, Overhead
Costs, Energy Efficiency. This paper also highlighting researchers’ key points, methodologies, and
evaluation criteria given by them over the past decade. It has been found that Hybrid algorithms
are the best choice for systems. Adaptability, fault tolerance, and energy efficiency of hybrid
algorithms consistently rank high across these metrics, making them ideal for modern, distributed
systems with dynamic workloads.