6th International Conference on Performance Evaluation Methodologies and Tools

Research Article

Mixing Properties of CSMA Networks on Partite Graphs

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  • @INPROCEEDINGS{10.4108/valuetools.2012.250264,
        author={Alessandro Zocca and Sem Borst and Johan van Leeuwaarden},
        title={Mixing Properties of CSMA Networks on Partite Graphs},
        proceedings={6th International Conference on Performance Evaluation Methodologies and Tools},
        publisher={IEEE},
        proceedings_a={VALUETOOLS},
        year={2012},
        month={11},
        keywords={csma networks throughput starvation interference graph asymptotic exponentiality mixing time conductance},
        doi={10.4108/valuetools.2012.250264}
    }
    
  • Alessandro Zocca
    Sem Borst
    Johan van Leeuwaarden
    Year: 2012
    Mixing Properties of CSMA Networks on Partite Graphs
    VALUETOOLS
    ICST
    DOI: 10.4108/valuetools.2012.250264
Alessandro Zocca1,*, Sem Borst1, Johan van Leeuwaarden1
  • 1: Eindhoven University of Technology
*Contact email: a.zocca@tue.nl

Abstract

We consider a stylized stochastic model for a wireless CSMA network. Experimental results in prior studies indicate that the model provides remarkably accurate throughput estimates for IEEE 802.11 systems. In particular, the model offers an explanation for the severe spatial unfairness in throughputs observed in such networks with asymmetric interference conditions. Even in symmetric scenarios, however, it may take a long time for the activity process to move between dominant states, giving rise to potential starvation issues. In order to gain insight in the transient throughput characteristics and associated starvation effects, we examine in the present paper the behavior of the transition time between dominant activity states. We focus on partite interference graphs, and establish how the magnitude of the transition time scales with the activation rate and the sizes of the various network components. We also prove that in several cases the scaled transition time has an asymptotically exponential distribution as the activation rate grows large, and point out interesting connections with related exponentiality results for rare events and meta-stability phenomena in statistical physics. In addition, we investigate the convergence rate to equilibrium of the activity process in terms of mixing times.