Estimating the Parameters of the Waxman Random Graph

  • Matthew RoughanEmail author
  • Jonathan Tuke
  • Eric Parsonage
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11631)


The Waxman random graph is useful for modelling physical networks where the increased cost of longer links means they are less likely to be built, and thus less numerous. The model has been in continuous use for over three decades with many attempts to match parameters to real networks, but only a few cases where a formal estimator was used. Even then the performance of the estimator was not evaluated. This paper presents both the first evaluation of formal estimators for these graphs, and a new Maximum Likelihood Estimator with O(e) computational complexity where e is the number of edges in the graph, and requiring only link lengths as input, as compared to all other algorithms which are \(\varOmega (n^2)\).



We would like to thank Lakhina et al. for providing the Internet dataset.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Matthew Roughan
    • 1
    Email author
  • Jonathan Tuke
    • 1
  • Eric Parsonage
    • 1
  1. 1.ARC Centre of Excellence for Mathematical and Statistical FrontiersUniversity of AdelaideAdelaideAustralia

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