DocumentCode :
2947657
Title :
Stochastic analysis of power-aware scheduling
Author :
Wierman, Adam ; Andrew, Lachlan L H ; Tang, Ao
Author_Institution :
Comput. Sci. Dept., California Inst. of Technol., Pasadena, CA
fYear :
2008
fDate :
23-26 Sept. 2008
Firstpage :
1278
Lastpage :
1283
Abstract :
Energy consumption in a computer system can be reduced by dynamic speed scaling, which adapts the processing speed to the current load. This paper studies the optimal way to adjust speed to balance mean response time and mean energy consumption, when jobs arrive as a Poisson process and processor sharing scheduling is used. Both bounds and asymptotics for the optimal speeds are provided. Interestingly, a simple scheme that halts when the system is idle and uses a static rate while the system is busy provides nearly the same performance as the optimal dynamic speed scaling. However, dynamic speed scaling which allocates a higher speed when more jobs are present significantly improves robustness to bursty traffic and mis-estimation of workload parameters.
Keywords :
Internet; energy consumption; power aware computing; processor scheduling; stochastic processes; Poisson process; dynamic speed scaling; energy consumption; mean energy consumption; mean response time; power-aware scheduling; processor sharing; stochastic analysis; Computer science; Costs; Delay; Energy consumption; Internet; Measurement; Power system modeling; Processor scheduling; Robustness; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication, Control, and Computing, 2008 46th Annual Allerton Conference on
Conference_Location :
Urbana-Champaign, IL
Print_ISBN :
978-1-4244-2925-7
Electronic_ISBN :
978-1-4244-2926-4
Type :
conf
DOI :
10.1109/ALLERTON.2008.4797707
Filename :
4797707
Link To Document :
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