Optimizing Cloud Computational Performance through Rock Hyrax Optimization Technique
Talla Sri Vandana, Pabbati Maruthi, V. Swetha, Saroja Kumar Rout, Kottu Santosh Kumar, Nilamadhab Mishra · 2025
The rapid jump in cloud computing usage has significantly increased energy consumption in data centers, raising concerns about operational costs and environmental sustainability. Traditional load-balancing algorithms prioritize performance and resource utilization but often neglect energy efficiency. The Energy Efficient Load Balancing Algorithm (EELBA) optimizes energy consumption while maintaining high reliability and performance. It dynamically distributes workloads based on energy efficiency, current server load, and predicted demand. The algorithm employs the Rock Hyrax Optimization (RHO) technique to regulate power usage and utilizes server consolidation to minimize active servers during low-demand periods. By concentrating workloads on fewer servers, EELBA enables idle servers to enter low-power states, significantly reducing energy consumption. Experimental results demonstrate that the algorithm achieves a 30% reduction in power consumption and improves resource utilization by 25% compared to conventional methods. It maintains an average response time of 2.3 ms, ensuring high service quality. The scalability of EELBA makes it suitable for both small and large cloud infrastructures, contributing to sustainable cloud computing by reducing the carbon footprint and lowering operational costs.