DocumentCode :
1938408
Title :
Dynamic right-sizing for power-proportional data centers
Author :
Lin, Minghong ; Wierman, Adam ; Andrew, Lachlan L H ; Thereska, Eno
Author_Institution :
California Inst. of Technol., Pasadena, CA, USA
fYear :
2011
fDate :
10-15 April 2011
Firstpage :
1098
Lastpage :
1106
Abstract :
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.
Keywords :
cloud computing; computer centres; power aware computing; power consumption; cloud services; dynamic right-sizing algorithm; lazy online algorithm; power consumption; power-proportional data centers; Data models; Delay; Heuristic algorithms; Optimization; Prediction algorithms; Servers; Switches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
INFOCOM, 2011 Proceedings IEEE
Conference_Location :
Shanghai
ISSN :
0743-166X
Print_ISBN :
978-1-4244-9919-9
Type :
conf
DOI :
10.1109/INFCOM.2011.5934885
Filename :
5934885
Link To Document :
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