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Stochastic Bounds and Histograms for Active Queues Management and Networks Analysis

  • Farah Aït-Salaht
  • Hind Castel-Taleb
  • Jean-Michel Fourneau
  • Nihal Pekergin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9845)

Abstract

We present an extension of a methodology based on monotonicity of various networking elements and measurements performed on real networks. Assuming the stationarity of flows, we obtain histograms (distributions) for the arrivals. Unfortunately, these distributions have a large number of values and the numerical analysis is extremely time-consuming. Using the stochastic bounds and the monotonicity of the networking elements, we show how we can obtain, in a very efficient manner, guarantees on performance measures. Here, we present two extensions: the merge element which combine several flows into one, and some Active Queue Management (AQM) mechanisms. This extension allows to study networks with a feed-forward topology.

Keywords

Performance evaluation Histograms Stochastic bounds Queue management 

Notes

Acknowledgement

This work was partially supported by grant ANR MARMOTE (ANR-12-MONU-0019) and DIGITEO.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Farah Aït-Salaht
    • 1
  • Hind Castel-Taleb
    • 2
  • Jean-Michel Fourneau
    • 3
  • Nihal Pekergin
    • 4
  1. 1.LIP6, Pierre et Marie Curie University, UMR7606ParisFrance
  2. 2.SAMOVAR, UMR 5157, Télécom Sud ParisEvryFrance
  3. 3.DAVID, Versailles St-Quentin UniversityVersaillesFrance
  4. 4.LACL, Paris Est-Créteil UniversityCréteilFrance

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