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Deciding on the Type of a Graph from a BFS

  • Xiaomin Wang
  • Matthieu Latapy
  • Michèle Soria
Part of the Communications in Computer and Information Science book series (CCIS, volume 116)

Abstract

The degree distribution of the Internet topology is considered as one of its main properties. However, it is only known through a measurement procedure which gives a biased estimate. This measurement may in first approximation be modeled by a BFS (Breadth-First Search) tree. We explore here our ability to infer the type (Poisson or power-law) of the degree distribution from such a limited knowledge. We design procedures which estimate the degree distribution of a graph from a BFS of it, and show experimentally (on models and real-world data) that this approach succeeds in making the difference between Poisson and power-law graphs.

Keywords

Random Graph Degree Distribution Average Degree Preferential Attachment Reconstruction Strategy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Xiaomin Wang
    • 1
  • Matthieu Latapy
    • 1
  • Michèle Soria
    • 1
  1. 1.LIP6-CNRS-UPMCParisFrance

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