Adaptive Control of Data Center Cooling using Deep Reinforcement Learning
Author:
Affiliation:
1. Lund University
2. Research Institutes of Sweden,RISE
3. Lund University/Ericsson Research
Funder
Vinnova
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9935058/9934873/09935071.pdf?arnumber=9935071
Reference25 articles.
1. Energy savings in data centers: A framework for modelling and control of servers’ cooling * *This work is supported by the Celtic Plus project SENDATE-Extend (C2015/3-3), the LTU Smart Machines and Materials project Control Oriented Computational Fluid Dynamics, the Swedish research council Norrbottens Forskningsråd project DISTRACT, and the Swedish Energimyndigheten E2B2 project Green Power.
2. Data center cooling using model-predictive control;lazic;Advances in neural information processing systems,2018
3. A survey on data center cooling systems: Technology, power consumption modeling and control strategy optimization
4. Deep Reinforcement Learning for Tropical Air Free-Cooled Data Center Control;van le;arXiv 2012 06834 [cs eess],2020
5. Invited Paper: Improving Data Center Efficiency Through Holistic Scheduling In Kubernetes
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