Incentive temperature control for green colocation data centers via reinforcement learning

Incentive temperature control for green colocation data centers via reinforcement learning

Increasing supply air temperatures is a rule-of-thumb approach to reduce the cooling energy usage of data centers (DCs). However, colocation DCs are short of incentive programs to move the tenants from the current over-cooling strategy despite the expanding allowable temperature ranges of the comput...

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Bibliographic Details
Main Authors: Wang, Rongrong, Le, Duc Van, Kang, Jikun, Tan, Rui, Liu, Xue
Other Authors: College of Computing and Data Science
Language:English
Published: 2024
Subjects:
Computer and Information Science
Colocation data center
Energy efficiency
Multi-agent reinforcement learning
Online Access:https://hdl.handle.net/10356/179463
https://iwqos2024.ieee-iwqos.org/sites/iwqos2024.ieee-iwqos.org/files/IWQoS2024-Full-Program.pdf

Internet

https://hdl.handle.net/10356/179463
https://iwqos2024.ieee-iwqos.org/sites/iwqos2024.ieee-iwqos.org/files/IWQoS2024-Full-Program.pdf

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