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Monitoring and modelling open compute servers
Luleå University of Technology, Sweden.
Luleå University of Technology, Sweden.
RISE - Research Institutes of Sweden, ICT, SICS.
Luleå University of Technology, Sweden.
Show others and affiliations
2017 (English)In: Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, Institute of Electrical and Electronics Engineers Inc. , 2017, p. 7177-7184Conference paper, Published paper (Refereed)
Abstract [en]

Energy efficient control of server rooms in modern data centers can help reducing the energy usage of this fast growing industry. Efficient control, however, cannot be achieved without: i) continuously monitoring in real-time the behavior of the basic thermal nodes within these infrastructures, i.e., the servers; ii) analyzing the acquired data to model the thermal dynamics within the data center. Accurate data and accurate models are indeed instrumental for implementing efficient data centers cooling strategies. In this paper we focus on a class of Open Compute Servers, designed in an open-source fashion and currently deployed by Facebook. We thus propose a set of methods for collecting real-time data from these platforms and a control-oriented model describing the thermal dynamics of the CPUs and RAMs of these servers as a function of both manipulable and exogenous inputs (e.g., the CPU utilization levels and the air mass flow produced by the server's fans). We identify the parameters of this model from real data and make the results available to other researchers.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2017. p. 7177-7184
Keywords [en]
data acquisition, Data center modelling, thermal control in data centers, thermal dynamics modelling, Dynamics, Energy efficiency, Energy utilization, Program processors, Control oriented models, Cooling strategy, CPU utilization, Data centers, Efficient control, Energy efficient, Exogenous input, Thermal dynamics, Industrial electronics
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:ri:diva-38042DOI: 10.1109/IECON.2017.8217256Scopus ID: 2-s2.0-85046630048ISBN: 9781538611272 (print)OAI: oai:DiVA.org:ri-38042DiVA, id: diva2:1297121
Conference
43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017, 29 October 2017 through 1 November 2017
Available from: 2019-03-19 Created: 2019-03-19 Last updated: 2019-03-20Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • text
  • asciidoc
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