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Distributed scheduling using simple learning machines
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DOI：10.1016/S0377-2217(97)00342-1.png)
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Abstract
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A new approach to develop parallel and distributed algorithms of scheduling tasks in parallel computers is proposed. A game theoretical model with the use of genetic-algorithms based learning machines called classifier systems as players in a game, serves as a theoretical framework of the approach. Experimental study of such a system shows its self-organizing features and the ability of collective behaviour. Following this approach a parallel and distributed scheduler is described. A simple version of the proposed scheduler has been implemented. Results of the experimental study of the scheduler demonstrate its high performance. (C) 1998 Elsevier Science B.V. All rights reserved.
Keywords:
parallel processing
scheduling
distributed artificial intelligence
game theory
adaptive processes
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