DocumentCode :
1929549
Title :
A fast genetic algorithm based static heuristic for scheduling independent tasks on heterogeneous systems
Author :
Menghani, Gaurav
Author_Institution :
Dept. of Comput. Eng., Thadomal Shahani Eng. Coll., Mumbai, India
fYear :
2010
fDate :
28-30 Oct. 2010
Firstpage :
113
Lastpage :
117
Abstract :
Scheduling of tasks in a heterogeneous computing (HC) environment is a critical task. It is also a well-known NP-complete problem, and hence several researchers have presented a number of heuristics for the same. The paper begins with introducing a new heuristic called Sympathy, and later a variant called Segmented Sympathy. A new Genetic Algorithm based heuristic using the Segmented Sympathy heuristic is proposed, which is aimed at improving over the speed and makespan of the implementation by Braun et al. Finally, the results of Simulation reveal that the proposed Genetic Algorithm gave up to 8.34% and on an average 3.42% better makespans. The new heuristic is also about 160% faster with respect to the execution time.
Keywords :
computational complexity; genetic algorithms; grid computing; NP-complete problem; genetic algorithm; heterogeneous computing; segmented sympathy heuristic; task scheduling; Conferences; Grid computing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel Distributed and Grid Computing (PDGC), 2010 1st International Conference on
Conference_Location :
Solan
Print_ISBN :
978-1-4244-7675-6
Type :
conf
DOI :
10.1109/PDGC.2010.5679877
Filename :
5679877
Link To Document :
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