DocumentCode :
3242148
Title :
An efficient optimization technique for task matching and scheduling in heterogeneous computing systems
Author :
Chuang, Po-Jen ; Wei, Chia-Hsin
Author_Institution :
Dept. of Electr. Eng., Tamkang Univ., Taipei Hsien, Taiwan
fYear :
2002
fDate :
17-20 Dec. 2002
Firstpage :
419
Lastpage :
424
Abstract :
A new optimization technique, the genetic annealing algorithm (GAA), is proposed to solve the task matching and scheduling problem in a heterogeneous computing system. The GAA is simple in design; it employs only the stir operation, a novel idea with the annealing concept, to locate optimal solutions. Experimental evaluation shows that compared with the genetic algorithm, simulated annealing and guided evolutionary simulated annealing approaches, the GAA yields constantly favorable performance in terms of speedup, running time, cost and complexity.
Keywords :
distributed processing; genetic algorithms; processor scheduling; simulated annealing; genetic algorithm; genetic annealing algorithm; guided evolutionary simulated annealing; heterogeneous computing system; optimization; task matching; task scheduling; Concurrent computing; Distributed computing; Processor scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Systems, 2002. Proceedings. Ninth International Conference on
ISSN :
1521-9097
Print_ISBN :
0-7695-1760-9
Type :
conf
DOI :
10.1109/ICPADS.2002.1183433
Filename :
1183433
Link To Document :
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