IWaOA: Resource Aware Scheduling Through Cloud Fog Computing Environment
Santhosh Kumar Medishetti, Ganesh Reddy Karri, Pillareddy Vamsheedhar Reddy, G. Soma Sekhar, Asha Varma Songa · 2023
In cloud and fog computing, task schedulingplays a role in maximizing the most of available resources and improving overall system efficiency. This work presents an improved form of the Walrus Optimization Algorithm (IWaOA) to handle task scheduling tasks in cloud fog computing (TS in CFC). By modifying the original algorithm in innovative ways, the suggested IWaOAis able to increase convergence and search efficiency by finding a happy medium between exploration and exploitation. Extensive tests using HPC2N real-world cloud fog computing datasets are used to compare IWaOA's performance to that of other popular task scheduling algorithms including WaOA,GAs, and PSOs. The outcomes prove that IWaOA is more effective than conventional methods in terms of task response time, makespan and throughput. The paper further evaluates IWaOA's scalability and robustness under different workloads and network conditions, demonstrating its flexibility and robustness in real-world cloud and fog computing settings. With the potential to increase throughput by 36%, reduce makespantime by 42%, and cut task response time by 26%, the improved Walrus Optimization Algorithm (IWaOA) Presents a favorable method for effectively tackling task scheduling challenges in cloud fog computing environments.