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Physical and Data-Driven Models for Edge Data Center Cooling System
RISE Research Institutes of Sweden, Digital Systems, Data Science.
RISE Research Institutes of Sweden, Digital Systems, Data Science.ORCID iD: 0000-0003-4293-6408
RISE Research Institutes of Sweden, Digital Systems, Data Science.ORCID iD: 0000-0002-9759-5594
Aalto University, Finland.
2020 (English)In: 2020 Swedish Workshop on Data Science, SweDS 2020, Institute of Electrical and Electronics Engineers Inc. , 2020Conference paper, Published paper (Refereed)
Abstract [en]

Edge data centers are expected to become prevalent providing low latency computing power for 5G mobile and IoT applications. This article develops two models for the complete cooling system of an edge data center: One model based on the laws of thermodynamics and one data-driven model based on LSTM neural networks. The models are validated against an actual edge data center experimental set-up showing root mean squared errors (RMSE) for most individual components below 1 °C over a simulation period of approximately 10 hours; which compares favourably to state-of-the-art models. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2020.
Keywords [en]
Cooling System, Data center, Edge, LSTM, Thermal Energy Storage
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-51947DOI: 10.1109/SweDS51247.2020.9275588Scopus ID: 2-s2.0-85099112779ISBN: 9781728192048 (print)OAI: oai:DiVA.org:ri-51947DiVA, id: diva2:1521247
Conference
2020 Swedish Workshop on Data Science, SweDS 2020, 29 October 2020 through 30 October 2020
Available from: 2021-01-22 Created: 2021-01-22 Last updated: 2023-06-07Bibliographically approved

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Brännvall, RickardGustafsson, Jonas

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  • apa
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  • de-DE
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  • nn-NB
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  • Other locale
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Output format
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  • asciidoc
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