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AIR
2005

Framework for Task Scheduling in Heterogeneous Distributed Computing Using Genetic Algorithms

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Framework for Task Scheduling in Heterogeneous Distributed Computing Using Genetic Algorithms
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. Experiments show that the algorithm outperforms each of the others and can achieve near optimal efficiency, with up to 100,000 tasks being scheduled.
Andrew J. Page, Thomas J. Naughton
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2005
Where AIR
Authors Andrew J. Page, Thomas J. Naughton
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