DocumentCode :
623621
Title :
Characterizing the impact of the workload on the value of dynamic resizing in data centers
Author :
Kai Wang ; Minghong Lin ; Ciucu, Florin ; Wierman, Adam ; Chuang Lin
Author_Institution :
Inst. of Software, Beijing, China
fYear :
2013
fDate :
14-19 April 2013
Firstpage :
515
Lastpage :
519
Abstract :
Energy consumption imposes a significant cost for data centers; yet much of that energy is used to maintain excess service capacity during periods of predictably low load. Resultantly, there has recently been interest in developing designs that allow the service capacity to be dynamically resized to match the current workload. However, there is still much debate about the value of such approaches in real settings. In this paper, we show that the value of dynamic resizing is highly dependent on statistics of the workload process. In particular, both slow timescale non-stationarities of the workload (e.g., the peak-to-mean ratio) and the fast time-scale stochasticity (e.g., the burstiness of arrivals) play key roles. To illustrate the impact of these factors, we combine optimization-based modeling of the slow time-scale with stochastic modeling of the fast time scale.
Keywords :
computer centres; energy consumption; power aware computing; statistical analysis; stochastic programming; dynamic data center resizing; energy consumption; fast time-scale stochasticity; optimization-based modeling; slow time scale nonstationarity; workload impact characterization; workload process; Data models; Delays; Heuristic algorithms; Optimization; Servers; Stochastic processes; Switches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
INFOCOM, 2013 Proceedings IEEE
Conference_Location :
Turin
ISSN :
0743-166X
Print_ISBN :
978-1-4673-5944-3
Type :
conf
DOI :
10.1109/INFCOM.2013.6566826
Filename :
6566826
Link To Document :
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