1st International ICST Conference on Simulation Tools and Techniques for Communications, Networks and Systems

Research Article

Using LiTGen, a realistic IP traffic model, to evaluate the impact of burstiness on performance

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  • @INPROCEEDINGS{10.4108/ICST.SIMUTOOLS2008.3065,
        author={Chlo\^{e} Rolland and Julien Ridoux and Bruno Baynat and Vincent Borrel},
        title={Using LiTGen, a realistic IP traffic model, to evaluate the impact of burstiness on performance},
        proceedings={1st International ICST Conference on Simulation Tools and Techniques for Communications, Networks and Systems},
        publisher={ICST},
        proceedings_a={SIMUTOOLS},
        year={2010},
        month={5},
        keywords={Traffic generator scaling behaviors second-order analysis performance evaluation},
        doi={10.4108/ICST.SIMUTOOLS2008.3065}
    }
    
  • Chloé Rolland
    Julien Ridoux
    Bruno Baynat
    Vincent Borrel
    Year: 2010
    Using LiTGen, a realistic IP traffic model, to evaluate the impact of burstiness on performance
    SIMUTOOLS
    ICST
    DOI: 10.4108/ICST.SIMUTOOLS2008.3065
Chloé Rolland1,*, Julien Ridoux2,*, Bruno Baynat1,*, Vincent Borrel1,*
  • 1: Université Pierre et Marie Curie – Paris VI LIP6/CNRS, UMR 7606 Paris, France
  • 2: ARC Special Research Center for Ultra- Broadband Information Networks (CUBIN), an affiliated program of National ICT Australia The University of Melbourne, Australia
*Contact email: Chloe.Rolland@lip6.fr, J.Ridoux@ee.unimelb.edu.au, Bruno.Baynat@lip6.fr, Vincent.Borrel@lip6.fr

Abstract

For practical reasons, network simulators have to be designed on traffic models as realistic as possible. This paper presents the evaluation of LiTGen, a realistic IP traffic model, for the generation of IP traffic with accurate time scale properties and performance. We confront LiTGen against real data traces1 using two methods of evaluation. These methods respectively allow to observe the causes and consequences of the traffic burstiness. Using a wavelet spectrum analysis, we first highlight the intrinsic characteristics of the traffic and show LiTGen’s ability to reproduce accurately the captured traffic correlation structures over a wide range of timescales. Then, a performance analysis based on simulations quantifies the impact of these characteristics on a simple queuing system, and demonstrates LiTGen’s ability to generate synthetic traffic leading to realistic performance. Finally, we conduct an investigation for a possible model reduction using memoryless assumptions.