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A Genetic Algorithm for Load Balancing in Parallel Query Evaluation for Deductive Relational Data Bases

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Artificial Neural Nets and Genetic Algorithms

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Abstract

Datalog is a query language for deductive databases. This language allows to evaluate a query incrementally on a network of processes. The tuples flow among them in parallel in order to compute the solution to the query. A major issue in this evaluation is the problem of assigning the processes to processors in a multiprocessors system. Not only load balancing is wanted but lowering the communication costs among the processors is crucial. We have tackled this problem by using a GA that works on a specific fitness function that allows to meet these goals. The techniques and results are presented here.

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References

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Authors and Affiliations

  1. Dpto. Lenguajes y Ciencias de la Computación, Universidad de Málaga, Plaza El Ejido s/n, 29013, Málaga, Spain

    E. Alba, J. F. Aldana & J. M. Troya

Authors
  1. E. Alba
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  2. J. F. Aldana
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  3. J. M. Troya
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© 1995 Springer-Verlag/Wien

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Alba, E., Aldana, J.F., Troya, J.M. (1995). A Genetic Algorithm for Load Balancing in Parallel Query Evaluation for Deductive Relational Data Bases. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_124

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  • DOI: https://doi.org/10.1007/978-3-7091-7535-4_124

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-82692-8

  • Online ISBN: 978-3-7091-7535-4

  • eBook Packages: Springer Book Archive

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