Load Balancing in Cloud Computing: A Simulation-Based Evaluation

Cloud computing has become a popular paradigm for delivering on-demand computing resources over the internet. One of the key challenges in cloud computing is load balancing, which ensures that computing resources are efficiently utilized, and applications are highly available. Load balancing is a crucial aspect of cloud computing that ensures optimal resource utilization while providing high performance to end users. This paper presents a simulation-based evaluation of three load balancing algorithms: Round Robin, Equally Spread, and Location-Aware based on four key criteria: Balancing Efficiency, Complexity, Suitability, and Fault Tolerance using the CloudAnalyst tool. We investigate the performance of these algorithms in a simulated cloud environment. Our results demonstrate that Equally Spread outperforms the other two algorithms in balancing efficiency and fault tolerance, while Location-Aware is better suited for complex cloud environments. Our simulation-based evaluation provides valuable insights into the performance of different load balancing algorithms in cloud computing environments based on key criteria. It highlights the importance of choosing an appropriate load balancing algorithm based on the application's specific requirements and the cloud environment for efficient resource utilization and improved performance.