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Dynamic task scheduling using genetic algorithms for heterogeneous distributed computing

Page, Andrew J. and Naughton, Thomas J. (2005) Dynamic task scheduling using genetic algorithms for heterogeneous distributed computing. In: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS’05). IEEE Computer Society, Denver, Colorado, 189a.1-189a.8. ISBN 0769523129

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An algorithm has been developed to dynamically schedule heterogeneous tasks on heterogeneous processors in a distributed system. The scheduler operates in an environment with dynamically changing resources and adapts to variable system resources. It operates in a batch fashion and utilises a genetic algorithm to minimise the total execution time. We have compared our scheduler to six other schedulers, three batch-mode and three immediate-mode schedulers. We have performed simulations with randomly generated task sets, using uniform, normal, and Poisson distributions, whilst varying the communication overheads between the clients and scheduler. We have achieved more efficient results than all other schedulers across a range of different scenarios while scheduling 10,000 tasks on up to 50 heterogeneous processors.

Item Type: Book Section
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Divisions: School of Computing > Staff Research and Publications
Depositing User: Caoimhe Ní Mhaicín
Date Deposited: 25 Mar 2014 09:18
Last Modified: 25 Mar 2014 10:30

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