Load balancing in cloud computing using cuckoo search algorithm

A competent cloud load balancer should modify its approach to the dynamic environment and the different types of tasks. Load balancing (LB) in cloud computing can be viewed as an optimisation problem. As load balancing in cloud is an NP-complete problem, the best solution cannot be found using gradient-based methods that look for optimal solutions to NP-complete problems in a reasonable amount of time. Therefore, evolutionary and meta-heuristic methods should be applied to tackle the load balancing issue. In this paper, a novel load balancing method based on cuckoo search (CS) algorithm is proposed. This method successfully distributes the load among the available virtual machines (VMs) while maintaining a low response time (RT) overall. Thus, its simulation is performed, and comparative simulation results reveal that the suggested approach outperforms existing tactics like round robin (RR), stochastic hill climbing (SHC), and genetic algorithm (GA). Copyright © 2024 Inderscience Enterprises Ltd.