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
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