Nature-Inspired Load Balancing Algorithms for Resource Allocation in Cloud Computing

Abstract

Cloud computing has revolutionized the way computing resources are provisioned and utilized. One of the key challenges in cloud computing is to allocate resources efficiently and effectively, which is known as load balancing. Nature-inspired algorithms have shown great potential in solving complex optimization problems, including load balancing. This research paper aims to study and compare the efficiency of various nature-inspired load balancing algorithms, such as Ant Colony Optimization, Particle Swarm Optimization, Genetic Algorithm, and Artificial Bee Colony. The paper analyzes these algorithms' features, benefits, limitations, and challenges and evaluates their effectiveness in load balancing in distributed systems. The research concludes that nature-inspired load balancing algorithms show promising results and can significantly improve the performance of distributed Cloud systems.