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