Transforming cooling optimization for green data center via deep reinforcement learning
Data center (DC) plays an important role to support services, such as e-commerce and cloud computing. The resulting energy consumption from this growing market has drawn significant attention, and noticeably almost half of the energy cost is used to cool the DC to a particular temperature. It is thu...
Main Authors: | Li, Yuanlong, Wen, Yonggang, Tao, Dacheng, Guan, Kyle |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/154224 |
Similar Items
-
Toward physics-guided safe deep reinforcement learning for green data center cooling control
by: Wang, Ruihang, et al.
Published: (2022) -
Joint IT-facility optimization for green data centers via deep reinforcement learning
by: Zhou, Xin, et al.
Published: (2022) -
Two-phase liquid-immersion data center cooling system : experimental performance and thermoeconomic analysis
by: Kanbur, Baris Burak, et al.
Published: (2021) -
Research Status and Future Development of Cooling Technologies for Green and Energy-Efficient Data Centers
by: Chen Xintuo, et al.
Published: (2022-08-01) -
Spatial access to cooling centers in the city of Boston
by: Neil K.R. Sehgal, et al.
Published: (2023-05-01)