DOA: Optimizing Resource Utilization in Cloud Environment Using Multi-Objective Meta-Heuristic Scheduling Algorithm
Sonam Marathe, T Neelima, G Anusha, Santhosh Kumar Medishetti
Abstract
Optimizing resource utilization in cloud environments is critical for enhancing system performance, minimizing costs, and improving energy efficiency. This paper introduces a novel approach using the Dingo Optimization Algorithm (DOA), a multi-objective meta-heuristic scheduling technique designed to address key challenges in cloud resource management. The DOA focuses on optimizing resource utilization by balancing load distribution, reducing energy consumption, and minimizing task completion time. Multiple objectives, such as makespan, energy efficiency, and throughput, are considered to ensure high resource utilization and Task Scheduling (TS) efficiency in dynamic cloud environments. Simulation results demonstrate that DOA outperforms traditional algorithms by achieving a 20% improvement in resource utilization, a 17% reduction in energy consumption, and a 15% decrease in task completion time. These findings validate the effectiveness of DOA in enhancing cloud resource management, providing a robust solution for optimizing multi-objective TS in cloud computing environments.