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Prediction of dynamical, nonlinear, and unstable process behavior

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Abstract

Process scheduling techniques consider the current load situation to allocate computing resources. Those techniques make approximations such as the average of communication, processing, and memory access to improve the process scheduling, although processes may present different behaviors during their whole execution. They may start with high communication requirements and later just processing. By discovering how processes behave over time, we believe it is possible to improve the resource allocation. This has motivated this paper which adopts chaos theory concepts and nonlinear prediction techniques in order to model and predict process behavior. Results confirm the radial basis function technique which presents good predictions and also low processing demands show what is essential in a real distributed environment.

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Authors and Affiliations

  1. Institute of Mathematics and Computer Science, University of São Paulo, São Carlos, SP, Brazil

    Rodrigo F. de Mello

  2. Department of Computer Science, St. Francis Xavier University, Antigonish, NS, Canada

    Laurence T. Yang

Authors
  1. Rodrigo F. de Mello
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  2. Laurence T. Yang
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Correspondence to Rodrigo F. de Mello.

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de Mello, R.F., Yang, L.T. Prediction of dynamical, nonlinear, and unstable process behavior. J Supercomput 49, 22–41 (2009). https://doi.org/10.1007/s11227-008-0215-z

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  • DOI: https://doi.org/10.1007/s11227-008-0215-z

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