AI-Powered Energy Efficient and Sustainable Cloud Networking

Abstract

The exponential growth of cloud computing has led to significant energy consumption, raising environmental and economic concerns. This study explores the role of artificial intelligence (AI) in enhancing energy efficiency in cloud networking. AI-driven approaches such as machine learning, deep learning, and reinforcement learning optimize resource allocation, workload balancing, and power management to minimize energy waste while maintaining performance. AI-powered predictive analytics enable real-time power demand forecasting, adaptive cooling, and efficient routing, contributing to reduced carbon footprints. Additionally, AI facilitates the integration of renewable energy sources by dynamically distributing computing tasks based on energy availability. This paper provides a comprehensive review of AI-based energy-saving strategies, highlighting key advancements, challenges, and future research directions. By leveraging intelligent automation and predictive modeling, AI is transforming cloud infrastructure into a sustainable and cost-effective digital ecosystem.