Binary Self-Adaptive Salp Swarm Optimization-Based Dynamic Load Balancing in Cloud Computing

In the recent era of cloud computing, huge demand for virtual resource provisioning requires mitigating challenges uniform load distribution as well efficient utilization among machines in datacenters. Salp swarm optimization is one simplest, yet metaheuristic techniques to balance VMs. The proposed methodology has incorporated self-adaptive procedures deal with unpredictable population tasks being executed Moreover, a sigmoid transfer function been integrated solve discrete problem assigned appropriate Thus, algorithm binary salp simulated and compared some approaches, like BSO, MPSO, SSO conflicting scheduling quality service parameters. It observed from result analysis that outperforms terms makespan, response time, degree imbalance while maximizing utilization.