1st International ICST Workshop On Wireless Network Measurement

Research Article

Towards Realistic Models of Wireless Workload

  • @INPROCEEDINGS{10.1109/WIOPT.2007.4480104,
        author={Stefan Karpinski and Elizabeth M. Belding and C. Almeroth},
        title={Towards Realistic Models of Wireless Workload},
        proceedings={1st International ICST Workshop On Wireless Network Measurement},
        keywords={Computer science  Internet  Laboratories  Measurement  Predictive models  Protocols  Space exploration  Space technology  Telecommunication traffic  Traffic control},
  • Stefan Karpinski
    Elizabeth M. Belding
    C. Almeroth
    Year: 2008
    Towards Realistic Models of Wireless Workload
    DOI: 10.1109/WIOPT.2007.4480104
Stefan Karpinski1,*, Elizabeth M. Belding1,*, C. Almeroth1,*
  • 1: Department of Computer Science University of California, Santa Barbara
*Contact email: sgk@cs.ucsb.edu, ebelding@cs.ucsb.edu, almeroth@cs.ucsb.edu


Performance predictions from wireless networking laboratory experiments rarely seem to match what is seen once technologies are deployed. We believe that one of the major factors hampering researchers' ability to make more reliable forecasts is the inability to generate realistic workloads. To redress this problem, we take a fundamentally new approach to measuring the realism of wireless traffic models. In this approach, the realism of a model is defined directly in terms of how accurately it reproduces the performance characteristics of actual network usage. This cuts through the Gordian knot of deciding which statistical features of traffic traces are significant. We demonstrate that common experimental traffic models, such as uniform constant bit-rate traffic (CBR), drastically misrepresent performance metrics at all levels of the protocol stack. We also define and explore the space of synthetic traffic models, thereby advancing the understanding of how different modeling techniques affect the accuracy of performance predictions. Our research takes initial steps that will ultimately lead to comprehensive, multi-level models of realistic wireless workloads.