Reproduction Mechanism with Squirrel Search Algorithm for Cloud Computing Resource Management

The cloud computing introduced to generate user requirements to access resource computing to users for purchasing cloud service as essential concept of on-demand resource sharing by highly internet-based applications. The resource management is significant in high-scale distributed computing which tackles complex optimization issues. Therefore, this research proposes a Reproduction Mechanism with Squirrel Search Algorithm (RMSSA) for cloud computing resource management. Primarily, multiple users access the shared resources and then RMSSA optimizes those resource through evaluation phase to estimate results. Based on this estimation, resources are updated and reallocated. This process is repeated iteratively for ensuring constant resource usage in optimization. The RMSSA enhances both efficiency and precision of resource allocation thereby enhancing overall performance. In RMSSA, the exploration and exploitation allow to discover unexplored opportunities while preventing local optima. It also determines the number of allocated resources based on fitness solutions that available cloud resources are used optimally. The makespan, cost, resource utilization, power consumption and throughput metrics are considered with different no. of tasks like 100, 300, 500, 700 and 900. The RMSSA obtains 420s, 920$ and 96.26% of makespan, cost and resource utilization for number of tasks of 500.