Accuracy and Scaling Phenomena in Internet Mapping

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dc.creatorClauset, Aaron
dc.creatorMoore, Cristopher
dc.date2004-10-04
dc.date.accessioned2026-07-07T09:31:43Z
dc.date.available2026-07-07T09:31:43Z
dc.descriptionA great deal of effort has been spent measuring topological features of the Internet. However, it was recently argued that sampling based on taking paths or traceroutes through the network from a small number of sources introduces a fundamental bias in the observed degree distribution. We examine this bias analytically and experimentally. For Erdos-Renyi random graphs with mean degree c, we show analytically that traceroute sampling gives an observed degree distribution P(k) ~ 1/k for k < c, even though the underlying degree distribution is Poisson. For graphs whose degree distributions have power-law tails P(k) ~ k^-alpha, traceroute sampling from a small number of sources can significantly underestimate the value of αwhen the graph has a large excess (i.e., many more edges than vertices). We find that in order to obtain a good estimate of alpha it is necessary to use a number of sources which grows linearly in the average degree of the underlying graph. Based on these observations we comment on the accuracy of the published values of alpha for the Internet.
dc.description4 pages, 3 figures; supercedes cond-mat/0407339 and contains scaling results on the accuracy of multi-source traceroute studies
dc.identifierhttps://arxiv.org/abs/cond-mat/0410059
dc.identifierhttp://arxiv.org/abs/cond-mat/0410059
dc.identifierPhys. Rev. Lett. 94, 018701 (2005)
dc.identifierdoi:10.1103/PhysRevLett.94.018701
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/158557
dc.subjectDisordered Systems and Neural Networks
dc.subjectNetworking and Internet Architecture
dc.subjectPhysics and Society
dc.titleAccuracy and Scaling Phenomena in Internet Mapping
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