Physical and Data-Driven Models for Edge Data Center Cooling System
2020 (English)In: 2020 Swedish Workshop on Data Science (SweDS), IEEE, 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
IEEE, 2020.
Keywords [en]
Edge, Data center, LSTM, Cooling System, Thermal Energy Storage, Mathematical model, Cooling, Data models, Data centers, Atmospheric modeling, Heat transfer, Thermal energy
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-81882DOI: 10.1109/SweDS51247.2020.9275588Scopus ID: 2-s2.0-85099112779OAI: oai:DiVA.org:ltu-81882DiVA, id: diva2:1507165
Conference
8th Swedish Workshop on Data Science (SweDS20), Luleå, Sweden, October 29-30, 2020
Funder
Vinnova, 17002
Note
ISBN för värdpublikation: 978-1-7281-9204-8
2020-12-072020-12-072022-04-13Bibliographically approved