ROA: Optimizing Scheduling Time and Load Balancing in Cloud Computing Environment

Abstract

In Cloud Computing (CC) environments, efficient Task Scheduling (TS) and load balancing are critical for maximizing resource utilization and minimizing service delays. This paper introduces a novel Red Kite Optimization Algorithm (ROA) aimed at optimizing task scheduling time and ensuring balanced workloads across distributed virtual machines. The ROA mimics the hunting and soaring behavior of red kites to dynamically assign tasks to the most appropriate resources based on current load and task requirements. Through enhanced exploration and exploitation phases, ROA significantly reduces task scheduling time, while maintaining load balancing across cloud nodes. Simulations conducted in CloudSim demonstrate that ROA outperforms traditional scheduling algorithms in terms of makespan, throughput, and load balancing improved by 18.3%, 16.4%, and 21.3% respectively, making it a promising solution for cloud service providers to achieve efficient and cost-effective operations.