DocumentCode :
2070409
Title :
Green task scheduling algorithms with energy reduction on heterogeneous computers
Author :
Zhang, Luna Mingyi ; Li, Keqin ; Zhang, Yan-Qing
Author_Institution :
Center for Adv. Studies in Sci., Math & Technol., Marietta, GA, USA
Volume :
1
fYear :
2010
fDate :
10-12 Dec. 2010
Firstpage :
560
Lastpage :
563
Abstract :
Two traditional heuristic task scheduling algorithms (STFCMEF-MS algorithm and LTFCMEF-MS algorithm) are developed to solve a multi-task scheduling problem on multiple computers to reduce energy consumption and finish required tasks before a deadline. Two new green task scheduling algorithms (STFCMEF-SA algorithm and LTFCMEF-SA algorithm) are proposed to solve the same problem. Since the energy is directly proportional to the number of instructions for each computer at a particular speed, the energy slope (a newly defined technical term) is a constant. Simulation results indicate that STFCMEF-SA algorithm and LTFCMEF-SA algorithm are more effective than STFCMEF-MS algorithm and LTFCMEF-MS algorithm in lowering energy consumption. Future work includes more theoretical analysis and more novel algorithms.
Keywords :
energy conservation; power aware computing; scheduling; LTFCMEF-MS algorithm; STFCMEF-MS algorithm; energy reduction; green task scheduling algorithms; heterogeneous computers; Analytical models; Computers; Green products; Heuristic algorithms; Power capacitors; Thyristors; Variable speed drives; Energy Reduction; Green Computing; Multi-Computer Scheduling; Power-Aware Methods; Task Scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Progress in Informatics and Computing (PIC), 2010 IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-6788-4
Type :
conf
DOI :
10.1109/PIC.2010.5687471
Filename :
5687471
Link To Document :
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