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Page, Andrew J. and Naughton, Thomas J. (2005) Framework for task scheduling in heterogeneous distributed computing using genetic algorithms. Artificial Intelligence Review, 24 (3-4). pp. 415-429.
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Abstract
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.
| Item Type: | Article |
|---|---|
| Additional Information: | This journal paper is an extended version of a conference paper presented at AICS'04 |
| Keywords: | distributed computing, genetic algorithms, task scheduling |
| Academic Unit: | Faculty of Science and Engineering > Computer Science |
| Item ID: | 1035 |
| Depositing User: | Andrew Page |
| Date Deposited: | 31 Jul 2008 |
| Journal or Publication Title: | Artificial Intelligence Review |
| Publisher: | Springer |
| Refereed: | Yes |
| URI: | https://mural.maynoothuniversity.ie/id/eprint/1035 |
| Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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