7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks

Research Article

Techniques for Simulation of Realistic Infrastructure Wireless Network Traffic

  • @INPROCEEDINGS{10.1109/WIOPT.2009.5291645,
        author={Caleb Phillips and Douglas Sicker and Dirk Grunwald and Suresh Singh},
        title={Techniques for Simulation of Realistic Infrastructure Wireless Network Traffic},
        proceedings={7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks},
        publisher={IEEE},
        proceedings_a={WIOPT},
        year={2009},
        month={10},
        keywords={wireless simulation performance infrastructure networking traffic classification},
        doi={10.1109/WIOPT.2009.5291645}
    }
    
  • Caleb Phillips
    Douglas Sicker
    Dirk Grunwald
    Suresh Singh
    Year: 2009
    Techniques for Simulation of Realistic Infrastructure Wireless Network Traffic
    WIOPT
    IEEE
    DOI: 10.1109/WIOPT.2009.5291645
Caleb Phillips1,*, Douglas Sicker1,*, Dirk Grunwald1,*, Suresh Singh2,*
  • 1: Department of Computer Science University of Colorado Boulder, Colorado, USA
  • 2: Department of Computer Science Portland State University Portland, Oregon, USA
*Contact email: caleb.phillips@colorado.edu, sicker@colorado.edu, grunwald@colorado.edu, singh@cs.pdx.edu

Abstract

In the design of wireless networking protocols and systems, simulation has become the primary form of initial validation and performance evaluation. Hence, ensuring the realism of simulators and simulation methods is fundamental for simulated results to be interpretable. In this paper, we provide a simulation framework for infrastructure wireless network traffic that allows researchers to use publicly available captured traces as a primary or background traffic source. We investigate the question of trace classification as a necessary task for these traces to be useful and apply our framework to a well-known power-saving application, showing that the use of real traffic provides substantially different results as compared to traffic generated from an application-specific fitted model or contrived source. Additionally, we show how trace classification provides unique insights into application behavior in both typical and extreme scenarios.