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Stochastic Bounds and Histograms for Network Performance Analysis

  • Farah Aït-Salaht
  • Hind Castel-Taleb
  • Jean-Michel Fourneau
  • Nihal Pekergin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8168)

Abstract

Exact analysis of queueing networks under real traffic histograms becomes quickly intractable due to the state explosion. In this paper, we propose to apply the stochastic comparison method to derive performance measure bounds under histogram-based traffics. We apply an algorithm based on dynamic programming to derive bounding traffic histograms on reduced state spaces. We indeed obtain easier bounding stochastic processes providing stochastic upper and lower bounds on buffer occupancy histograms (queue length distributions) for finite queue models. We evaluate the proposed method under real traffic traces, and we compare the results with those obtained by an approximative method. Numerical results illustrate that the proposed method provides more accurate results with a tradeoff between computation time and accuracy. Moreover, the derived performance bounds are very relevant in network dimensioning.

Keywords

Network QoS Histogram-based traffic models Stochastic Comparison 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Farah Aït-Salaht
    • 1
  • Hind Castel-Taleb
    • 2
  • Jean-Michel Fourneau
    • 1
  • Nihal Pekergin
    • 3
  1. 1.UMR CNRS 8144PRiSM, Univ. Versailles St QuentinVersaillesFrance
  2. 2.SAMOVAR, UMR 5157Télécom Sud ParisEvryFrance
  3. 3.LACLUniv. Paris Est-CréteilFrance

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