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Anova-Informed Decision Trees for Voice Applications over Manets

  • Mouna Benaissa
  • Vincent Lecuire
  • D.W. McClary
  • Violet R. Syrotiuk
Conference paper
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 162)

Abstract

Both real-time multimedia and mobile networks present challenges ripe for new analysis techniques. We examine the applicability of statistical design of experiments and inductive learning theory in the prediction of delay for real-time audio transmissions over mobile ad hoc networks. Utilizing analysis of variance methods and simple decision tree agents, we find both significant factor interaction between traffic load and node mobility as well as a dramatic reduction in error percentage in prediction of end-to-end delay.

Keywords

Node Mobility Medium Access Control Traffic Load Medium Access Control Protocol Factor Interaction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© International Federation for Information Processing 2005

Authors and Affiliations

  • Mouna Benaissa
    • 1
  • Vincent Lecuire
    • 1
  • D.W. McClary
    • 2
  • Violet R. Syrotiuk
    • 2
  1. 1.CRAN, CNRS UMR 7039Henri Poincare-Nancy I UniversityVandoeuvre-les-Nancy CedexFrance
  2. 2.Department of Computer Science & EngineeringArizona State UniversityTempeUSA

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