AI-Driven Energy Optimization for Virtual Machines in Cloud Computing

DOI

10.2991/978-94-6463-872-1_19How to use a DOI?

Keywords

AI-driven optimization; cloud computing; energy efficiency; machine learning; resource management; green infrastructure; hybrid energy solutions

Abstract

Cloud computing has become the backbone of modern digital infrastructure, driving everything from enterprise business applications to consumer services. But strong demand for cloud services has driven up energy consumption, spurring operational costs and threatening environmental sustainability. When it comes to energy efficiency, virtual machines or VMs, the most important and fundamental unit of resource management in cloud environments, hold enormous opportunities but also pitfalls. This study study evaluates the contributions of Artificial intelligence (AI) on these areas for the efficient utilisation of energy in cloud data centres through Virtual Machines (VMs). The use of AI like machine learning, deep learning, and reinforcement learning enables components like dynamic resource allocation, load prediction, and intelligent load balancing that helps minimize the used energy while maintaining reliability. Artificial intelligence based approaches such as energy-aware Virtual Machine placement, predictive management of busy servers or real-time tracking of energy consumption can be applied to overcome energy inefficiencies. An additional boost in greener operations can come from integrating renewable sources into cloud systems through the help of AI. Examples of AI applications responsible for lowering energy expenses and increasing efficiency come from SOURCE companies such as Google and Amazon. Many future trends are addressed in the paper, including the autonomous management of AI driven Data centers and Smart Energy powered by IoT, along with challenges that EI faces while implementing AI for energy optimization. Human-level sentence: It highlights the game-changing importance of Artificial Intelligence in reaching sustainable, green cloud computing environments focused more on the energy savings of virtual machines.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ashish Semwal
AU  - Manmohan Singh Rauthan
AU  - Varun Barthwal
AU  - Sagar Samrat Shah
AU  - Kuldeep Singh
AU  - Nisha Pokhriyal
PY  - 2025
DA  - 2025/11/04
TI  - AI-Driven Energy Optimization for Virtual Machines in Cloud Computing
BT  - Proceedings of the 2nd International Conference on Sustainable Business Practices and Innovative Models (ICSBPIM-2025)
PB  - Atlantis Press
SP  - 254
EP  - 277
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-872-1_19
DO  - 10.2991/978-94-6463-872-1_19
ID  - Semwal2025
ER  -