Energy-Aware Task Scheduling in Cloud Computing Environments

Abstract

Efficient task scheduling is critical for reducing energy consumption and improving resource utilization in cloud data centers. This paper presents an energy-aware scheduling algorithm that dynamically allocates tasks based on workload conditions and power efficiency metrics. The proposed method minimizes idle resource consumption while maintaining Quality of Service requirements. Simulation results show reduced energy usage, lower operational costs, and improved system performance compared to traditional scheduling approaches. The paper emphasizes the importance of sustainable resource management in future cloud infrastructures.