FTTA: Optimizing Resource Utilization in Cloud Environment using Meta-Heuristic Scheduling Algorithm
C. Bennett, Rohan Reddy Oduru, Dominick McLaughlin, Lokesh Parvathaneni, Noah Bryan Riquelme, Santhosh Kumar Medishetti
Abstract
In Cloud Computing (CC) environment, optimizing resource utilization is critical for enhancing performance, reducing energy consumption, and minimizing operational costs. This paper introduces a novel Football Team Training Algorithm (FTTA) designed to improve resource allocation and utilization in dynamic cloud environments. Inspired by the collaborative and strategic dynamics of football team training, FTTA models tasks as players, assigning them to available cloud resources based on real-time workload and performance metrics. The algorithm effectively balances exploration and exploitation, ensuring that resources are allocated optimally while minimizing underutilization or overloading. Simulation results demonstrate that FTTA improves resource utilization by 20.6%, reduces task completion time by 16%, and enhances throughput by 18.4% when compared to traditional algorithms. These improvements make FTTA a promising approach for cloud service providers aiming to optimize resource management and deliver superior quality of service (QoS).