Thermal Modeling and Thermal-Aware Energy Saving Methods for Cloud Data Centers: A Review
Jianpeng Lin, Weiwei Lin, Huikang Huang, Wenjun Lin, Keqin Li
Abstract
Constructing energy-efficient cloud data centers (CDCs) is an essential path for the further expansion of cloud computing. As one of the core subsystems of a data center, the cooling system provides a reliable thermal environment for the safe operation of IT equipment while posing a huge energy consumption and carbon emission problem. Thus, it is evident that optimizing energy management of cooling systems with considerable energy-saving potential will be essential to realize the green and low-carbon development of CDCs. Therefore, to track the research progress of data center thermal management technologies, this review focuses on two research efforts: thermal modeling and thermal-aware energy saving methods. First, various thermal modeling approaches are reviewed for air-cooled and liquid-cooled data centers. Secondly, a comprehensive review of existing advanced thermal management approaches is conducted from three perspectives: thermal-aware IT load scheduling, cooling system control optimization, and joint optimization of the IT and cooling systems. Finally, we put forward some open issues and future research directions for thermal management that have not been completely solved. This review aims to provide reasonable suggestions to enhance cooling energy efficiency and further promote the transformation of CDCs to lower energy consumption and sustainable direction.