AI-Enabled Energy-Efficient Resource Management in Cloud Computing

Abstract

Cloud computing provides flexible and scalable computing resources, but the continuous operation of large-scale data centers can result in significant energy consumption. Efficient energy management is therefore an important aspect of sustainable cloud computing. Traditional resource management approaches may allocate resources without fully considering energy consumption, resulting in unnecessary power usage during periods of low workload. Artificial Intelligence (AI) provides opportunities to improve energy efficiency by analyzing workload patterns, predicting resource requirements, and dynamically adjusting cloud resources. This paper presents an AI-enabled framework for energy-efficient resource management in cloud computing environments. The proposed approach monitors workload intensity, predicts future resource requirements, and dynamically manages virtual machines and computing resources according to demand. The framework aims to reduce unnecessary resource usage while maintaining acceptable application performance. An experimental evaluation can be performed using simulated cloud workloads with different resource utilization levels. The expected results indicate that AI-based resource management can reduce energy consumption by improving resource utilization and dynamically adapting infrastructure to workload changes. The study demonstrates the potential of Artificial Intelligence for developing more sustainable and energy-efficient cloud computing environments.