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Genetic fuzzy rule-based scheduling system for grid computing in virtual organizations

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Abstract

One of the most challenging problems when facing the implementation of computational grids is the system resources effective management commonly referred as to grid scheduling. A rule-based scheduling system is presented here to schedule computationally intensive Bag-of-Tasks applications on grids for virtual organizations. There exist diverse techniques to develop rule-base scheduling systems. In this work, we suggest the joining of a gathering and sorting criteria for tasks and a fuzzy scheduling strategy. Moreover, in order to allow the system to learn and thus to improve its performance, two different off-line optimization procedures based on Michigan and Pittsburgh approaches are incorporated to apply Genetic Algorithms to the fuzzy scheduler rules. A complex objective function considering users differentiation is followed as a performance metric. It not only provides the conducted system evaluation process a comparison with other classical approaches in terms of accuracy and convergence behaviour characterization, but it also analyzes the variation of a wide set of evolution parameters in the learning process to achieve the best performance.

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Acknowledgments

This work has been financially supported by the Andalusian Government (Research Project P06-SEJ-01694).

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  1. Telecommunication Engineering Department, Jaen University, Alfonso X el Sabio, 28 Linares, Jaen, Spain

    R. P. Prado, S. García-Galán, A. J. Yuste & J. E. Muñoz Expósito

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  1. R. P. Prado
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  2. S. García-Galán
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  3. A. J. Yuste
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  4. J. E. Muñoz Expósito
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Correspondence to R. P. Prado.

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Prado, R.P., García-Galán, S., Yuste, A.J. et al. Genetic fuzzy rule-based scheduling system for grid computing in virtual organizations. Soft Comput 15, 1255–1271 (2011). https://doi.org/10.1007/s00500-010-0660-5

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