Load Balancing Algorithms for Cloud Computing Performance: A Review

This paper delves into the critical role of load balancing in optimizing cloud computing performance, emphasizing the equitable distribution of workloads through virtual machines (VMs). Load balancing as a service (LaaS) is essential for managing data traffic, preventing resource underutilization, or overuse. Static and dynamic load balancing algorithms, exemplified by round robin, Min-Min, Max-Min, central queue, local queue, and least connection, offer varied approaches with trade-offs in adaptability and system overhead. The comparative analysis highlights the importance of selecting algorithms based on specific system requirements, considering parameters such as reliability, fault tolerance, scalability, and overall performance. Algorithms like central queue, local queue, and least connection demonstrate high reliability and fault tolerance, but the choice ultimately hinges on the unique needs of the system, necessitating experimentation, or simulation for precise algorithm selection.