DocumentCode :
2791829
Title :
An Energy-Efficient Framework for Large-Scale Parallel Storage Systems
Author :
Zong, Ziliang ; Briggs, Matt ; O´Connor, Nick ; Qin, Xiao
Author_Institution :
Dept. of Comput. Sci., New Mexico Inst. of Min. & Technol., Socorro, NM
fYear :
2007
fDate :
26-30 March 2007
Firstpage :
1
Lastpage :
7
Abstract :
Huge energy consumption has become a critical bottleneck for further applying large-scale cluster systems to build new data centers. Among various components of a data center, storage subsystems are one of the biggest consumers of energy. In this paper, we propose a novel buffer-disk based framework for large-scale and energy-efficient parallel storage systems. To validate the efficiency of the proposed framework, a buffer-disk scheduling algorithm is designed and implemented. Our algorithm can provide more opportunities for underlying disk power management schemes to save energy by keeping a large number of idle data disks in sleeping mode as long as possible. The trace-driven simulation results based on a revised disksim simulator show that this new framework can significantly improves the energy efficiency of large-scale parallel storage systems.
Keywords :
buffer storage; disc storage; parallel processing; power aware computing; scheduling; buffer-disk scheduling algorithm; data centers; disk power management schemes; disksim simulator; energy-efficient parallel storage systems; large-scale parallel storage systems; trace-driven simulation; Algorithm design and analysis; Buffer storage; Computer science; Energy consumption; Energy efficiency; Energy storage; High performance computing; Humans; Large-scale systems; Scheduling algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International
Conference_Location :
Long Beach, CA
Print_ISBN :
1-4244-0910-1
Electronic_ISBN :
1-4244-0910-1
Type :
conf
DOI :
10.1109/IPDPS.2007.370559
Filename :
4228287
Link To Document :
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