Soft Computing

, Volume 15, Issue 7, pp 1255–1271 | Cite as

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

  • R. P. PradoEmail author
  • S. García-Galán
  • A. J. Yuste
  • J. E. Muñoz Expósito
Original Paper


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.


Grid computing Scheduling Fuzzy rule-based systems Evolutionary algorithms Genetic fuzzy systems 



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


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • R. P. Prado
    • 1
    Email author
  • S. García-Galán
    • 1
  • A. J. Yuste
    • 1
  • J. E. Muñoz Expósito
    • 1
  1. 1.Telecommunication Engineering DepartmentJaen UniversityJaenSpain

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