Improved Cat Swarm Optimization Algorithm for Load Balancing in the Cloud Computing Environment

Recently, cloud computing has gained recognition as a powerful tool for providing clients with flexible platforms, software services, and cost-effective infrastructures. Cloud is form of distributed that allows users to store process data in virtual environment instead physical server. This beneficial because it businesses quickly scale up or down their capacity, reducing the need invest expensive hardware. As tasks continue grow exponentially usage services increases, scheduling these across diverse machines poses challenging NP-hard optimization problem substantial requirements, including optimal resource utilization levels, short execution time, reasonable implementation cost. The issue consequently been addressed using variety meta-heuristic algorithms. In this paper, we propose new load-balancing approach Cat Swarm Optimization (CSO) algorithm order distribute load among various servers within center. Statistical analyses indicate our superior previous research regard energy consumption, makespan, time required 30%, 35%, 40%, respectively.