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A testbed and data yields for studying data center energy efficiency and reliability

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Published:04 November 2018Publication History

ABSTRACT

Many data centers still adopt low temperature setpoints, resulting in high energy consumption of their cooling systems. In our ongoing research project, we have built a data center testbed consisting of three test rooms hosting servers and network equipment. In particular, the testbed is equipped with cooling, heating, and ventilation systems that are under our full control. Thus, we can operate the testbed in a wide range of server room conditions. The test rooms and servers are instrumented with hardware and software sensors monitoring more than 200 measurement points. An extensive test plan is being executed to collect a large volume of data to understand the impact of environmental conditions on server's computing performance and reliability as well as the energy efficiency of the testbed. The results will provide important guidelines for building and operating energy-efficient data centers. We will work with relevant authorities towards providing the data collected from the testbed to the research communities.

References

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  2. Nosayba El-Sayed, Ioan A. Stefanovici, George Amvrosiadis, Andy A. Hwang, and Bianca Schroeder. 2012. Temperature Management in Data Centers: Why Some (Might) Like It Hot. In Proc. SIGMETRICS. 163--174. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. R. Khanna, H. Liu, and T. Rangarajan. 2014. Wireless Data Center Management: Sensor Network Applications and Challenges. IEEE Microw. Mag. 15, 7 (2014), S45--S60.Google ScholarGoogle ScholarCross RefCross Ref
  4. Jie Liu and Andreas Terzis. 2012. Sensing Data Centers for Energy Efficiency. Philosophical Transactions of The Royal Society A 370 (2012), 136--157.Google ScholarGoogle ScholarCross RefCross Ref

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  • Published in

    cover image ACM Conferences
    DATA '18: Proceedings of the First Workshop on Data Acquisition To Analysis
    November 2018
    36 pages
    ISBN:9781450360494
    DOI:10.1145/3277868

    Copyright © 2018 ACM

    © 2018 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 4 November 2018

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