TY - GEN
T1 - Methods and techniques for measuring and improving data center best practices
AU - Hamann, Hendrik F.
AU - Schappert, Michael
AU - Iyengar, Madhusudan
AU - Van Kessel, Theodore
AU - Claassen, Alan
PY - 2008
Y1 - 2008
N2 - Here we present a novel, measurement-based method for characterizing and improving the energy efficiency of a data center (DC). The technique not only yields a clear set of measurement-based best practices metrics, but also provides clear guidance to a DC manager to substantially improve the DC energy efficiency. We describe a technology which exploits the superiority of fast and massive parallel data collection using the Mobile Measurement Technology (MMT) [1] to drive towards quantitative, measurement-driven DC best practices implementation. A large representative raised-floor DC is mapped by the MMT methodology readily yielding the DC layout, very detailed 3D temperature distributions, flows and other relevant physical parameters of the specific facility. The data is used to calculate key metrics (horizontal and vertical hotspots, targeted air flow, plenum temperature, air conditioning unit utilization and flow levels). These metrics provide insights into the sources of energy inefficiencies of the current DC setup, and systematically guide DC managers to improve various best practice aspects in the specific DC. It is shown that significant energy reductions can be achieved utilizing the above described best practices methodology.
AB - Here we present a novel, measurement-based method for characterizing and improving the energy efficiency of a data center (DC). The technique not only yields a clear set of measurement-based best practices metrics, but also provides clear guidance to a DC manager to substantially improve the DC energy efficiency. We describe a technology which exploits the superiority of fast and massive parallel data collection using the Mobile Measurement Technology (MMT) [1] to drive towards quantitative, measurement-driven DC best practices implementation. A large representative raised-floor DC is mapped by the MMT methodology readily yielding the DC layout, very detailed 3D temperature distributions, flows and other relevant physical parameters of the specific facility. The data is used to calculate key metrics (horizontal and vertical hotspots, targeted air flow, plenum temperature, air conditioning unit utilization and flow levels). These metrics provide insights into the sources of energy inefficiencies of the current DC setup, and systematically guide DC managers to improve various best practice aspects in the specific DC. It is shown that significant energy reductions can be achieved utilizing the above described best practices methodology.
KW - Data center cooling
KW - Energy efficiency
UR - https://www.scopus.com/pages/publications/50949115462
U2 - 10.1109/ITHERM.2008.4544390
DO - 10.1109/ITHERM.2008.4544390
M3 - Conference contribution
AN - SCOPUS:50949115462
SN - 9781424417018
T3 - 2008 11th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems, I-THERM
SP - 1146
EP - 1152
BT - 2008 11th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems, I-THERM
T2 - 2008 11th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems, I-THERM
Y2 - 28 May 2008 through 31 May 2008
ER -