Dynamic right-sizing for power-proportional data centers

Power consumption imposes a significant cost for data centers implementing cloud services, yet much of that power is used to maintain excess service capacity during periods of predictably low load. This paper investigates how much can be saved by dynamically `right-sizing' the data center by tu...

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Bibliographic Details
Published in:2011 Proceedings IEEE INFOCOM pp. 1098 - 1106
Main Authors: Minghong Lin, Wierman, A., Andrew, L. L. H., Thereska, E.
Format: Conference Proceeding
Language:English
Published: IEEE 01.04.2011
Subjects:
Data models
Delay
Heuristic algorithms
Optimization
Prediction algorithms
Servers
Switches
ISBN:1424499194, 9781424499199
ISSN:0743-166X
Online Access:Get full text
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Summary:Power consumption imposes a significant cost for data centers implementing cloud services, yet much of that power is used to maintain excess service capacity during periods of predictably low load. This paper investigates how much can be saved by dynamically `right-sizing' the data center by turning off servers during such periods, and how to achieve that saving via an online algorithm. We prove that the optimal offline algorithm for dynamic right-sizing has a simple structure when viewed in reverse time, and this structure is exploited to develop a new `lazy' online algorithm, which is proven to be 3-competitive. We validate the algorithm using traces from two real data center workloads and show that significant cost-savings are possible.
ISBN:1424499194
9781424499199
ISSN:0743-166X
DOI:10.1109/INFCOM.2011.5934885