Swarm Intelligence Approach for Load Balancing In Distributed Computing Systems using Firefly Algorithm

Load balancing in distributed computing systems is crucial for optimal resource utilization and performance enhancement. Swarm intelligence algorithms offer promising solutions due to their ability to mimic collective behavior observed in nature. This study proposes a novel approach for load balancing using the Firefly Algorithm, a bio-inspired optimization technique based on the flashing behavior of fireflies. The algorithm is applied to dynamically distribute tasks among nodes in a distributed computing environment. The contribution lies in adapting the Firefly Algorithm specifically for load balancing purposes in distributed computing systems. The study explores the effectiveness of this approach in improving system performance and resource utilization. Experimental evaluations demonstrate the efficacy of the proposed approach in achieving load balancing objectives. The Firefly Algorithm effectively redistributes tasks among nodes, reducing processing delays and improving overall system efficiency. Comparative analysis against existing methods showcases the superiority of the proposed approach in various performance metrics.