International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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AI-Driven Energy Management in Green Cloud Computing: A Systematic Review

Author(s) Prof. Dr. Sugandha Goel, Dr. Monika Dixit Bajpai
Country India
Abstract The rapid expansion of cloud computing has significantly increased energy consumption, now accounting for an estimated 2–4% of global carbon dioxide emissions (Jones, 2023). In response, Artificial Intelligence (AI) has become a vital enabler in enhancing energy efficiency within the framework of Green Cloud Computing (GCC). This comprehensive review draws insights from 35 scholarly publications spanning from 2015 to 2024, focusing on how AI techniques are applied to energy management in cloud environments. The analysis highlights the use of Machine Learning (ML) methods—such as LSTM and Random Forest—for accurate workload prediction and allocation. It also examines Deep Reinforcement Learning (DRL) models like Deep Q-Networks (DQN) and Proximal Policy Optimization (PPO) for dynamically adjusting resource usage in response to changing system demands. Additionally, Federated Learning (FL) is explored as a strategy for distributed optimization, reducing the need for centralized data processing. The findings reveal that AI applications can lower data centre energy consumption by 20% to 40% (Zhang et al., 2022), though issues such as real-time adaptability and system compatibility remain barriers. The review concludes by identifying future research directions, including the integration of quantum-enhanced AI and edge-cloud collaboration to further improve energy efficiency and sustainability in cloud infrastructures.
Keywords Artificial Intelligence, Green Cloud Computing, Energy Efficiency, Deep Reinforcement learning, Sustainable Data Centres
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 3, May-June 2025
Published On 2025-06-19
DOI https://doi.org/10.36948/ijfmr.2025.v07i03.48659
Short DOI https://doi.org/g9qw9d
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