Cloud computing enables convenient access to computational resources, but managing them efficiently remains a challenge. Load balancing optimises performance and resource usage, but achieving efficiency in large-scale environments is complex. In this paper, the Enhancing Load Balancing Efficiency in Cloud Computing utilising Binary Kepler and Slap Swarm Optimised Approach (ELBF-CC-BK-SSOA) is proposed to overcome the challenges. This research proposes Binary Kepler optimisation (BKOA) as a load balancing solution for cloud computing. Initially, the System Efficiency using BKOA is used to find the best solution to problems. Next, resource allocation using MemeticSalp Swarm Optimisation Algorithm (MSSOA) is employed to distribute available resources. Experimental results demonstrate that ELBF-CC-BK-SSOA outperforms existing methods by achieving 33.13% lower response time, 28.27% higher throughput, 24.12% reduced CPU utilisation and 26.19% increased cost efficiency compared to existing techniques. This highlights the model's effectiveness in enhancing cloud performance, resource utilisation and reducing operational costs for dynamic cloud environments.
Kadu et al. (Thu,) studied this question.