Energy-Efficient Resource Allocation in Green Cloud Infrastructure

Abstract

Energy-efficient resource allocation in green cloud infrastructure is pivotal for reducing operational costs and environmental impact while maintaining Quality of Service (QoS). This manuscript investigates a novel heuristic-based allocation algorithm designed to minimize energy consumption across virtualized data centers powered partly by renewable energy sources. Performance is evaluated through simulation in a heterogeneous cloud environment, comparing the proposed approach against baseline and existing heuristic methods. Statistical analysis of energy usage, carbon emissions, resource utilization, and latency demonstrates significant improvements using the proposed algorithm. Results indicate up to 18% reduction in energy consumption and a 22% decrease in carbon footprint without compromising application performance.

The study concludes with detailed recommendations for integrating renewable-aware scheduling policies, discusses practical deployment considerations such as integration with existing cloud orchestration frameworks, and highlights future research avenues, including adaptive learning mechanisms and incorporation of energy storage solutions.