Sabrina Spatari
Dept. Of Civil, Architectural, and Environmental Engineering, Drexel University, Philadelphia, USA
Nagarajan Kandasamy
Dept. Of Electrical and Computer Engineering, Drexel University, Philadelphia, USA
Dara Kusic
Coriell Institute, Camden, USA
Eugenia V. Ellis
Dept. Of Architecture & Interiors, Drexel University, Philadelphia, USA
Jin Wen
Dept. of Civil, Architectural, and Environmental Engineering, Drexel University, Philadelphia, USA
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http://dx.doi.org/10.3384/ecp11057913Published in: World Renewable Energy Congress - Sweden; 8-13 May; 2011; Linköping; Sweden
Linköping Electronic Conference Proceedings 57:22, p. 913-920
Published: 2011-11-03
ISBN: 978-91-7393-070-3
ISSN: 1650-3686 (print), 1650-3740 (online)
Data centers have become an essential operational component of nearly every sector of the economy; and as a result growing consumers of energy and emitters of greenhouse gases (GHGs). Developing strategies for optimizing power usage and reducing the associated life cycle GHG emissions are critical priorities for meeting climate policy objectives. We investigate data center power management through virtualization; a technique that consolidates data center workloads onto fewer computing resources within a data center and deploys computing resources only as needed. Based on an experimentally validated dynamic resource provisioning framework applied to a small scale computing cluster at Drexel University that employed lookahead control; a control scheme using virtualization demonstrated a 25% reduction in power consumption over a 24-hour period. Using the power savings results from the virtualization experiments; and extrapolating those savings to a medium-sized data center that hosts 500 servers; we estimate the avoided life cycle GHG emissions for implementing a virtualization strategy in hourly time-steps for marginal and average electricity units over a 24-hour day during the month of August; when electricity loads are typically highest for the year. Results from this work show virtualization could avoid the emission of approximately 0.8 to 1.2 metric tons CO2e/day.
Energy; Power management; Buildings; Information technology; Life cycle assessment
[1] McKinsey & Co.; Report: Revolutionizing Data Center Efficiency; 2008.
[2] D. Kusic and N. Kandasamy; "Risk-Aware Limited Lookahead Control for Dynamic Resource Provisioning in Enterprise Computing Systems;" Cluster Computing: Special Issue on Autonomic Computing; v. 10; n. 7; Kluwer Academic Publishers; Dec. 2007; pp. 395-408.
[3] Kusic; D.; J. O. Kephart; J. E. Hanson; N. Kandasamy; and G. Jiang; “Power and Performance Management of Virtualized Computing Environments via Lookahead Control;’’ Cluster Computing; vol. 12; no. 1; pp. 1-15; Springer Netherlands; March 2009.
[4] D. Kusic; J. Kephart; J. Hanson; N. Kandasamy and G. Jiang; "Power and Performance Management of Virtualized Computing Environments via Lookahead Control;" Proc. IEEE Conf. on Autonomic Computing (ICAC’08); Chicago; IL; Jun. 2008; pp 3-12.
[5] ISO; 2006. ISO 14044: Environmental management — Life cycle assessment — Requirements and guidelines. International Standards Organization; Geneva.
[6] Ekvall; T.; Weidema; B.P.; 2004. System boundaries and input data in consequential life cycle inventory analysis. International Journal of Life Cycle Assessment 9; 161-171.
doi: 10.1007/BF02994190.
[7] Kim; S.; Dale; B.; “Life Cycle Inventory Information of the United States Electricity System;” (11/17 pp). The International Journal of Life Cycle Assessment 2005; 10; (4); 294-304. doi: 10.1065/lca2004.09.176.
