Systematic Topology Analysis and Generation Using Degree Correlations

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dc.creatorMahadevan, Priya
dc.creatorKrioukov, Dmitri
dc.creatorFall, Kevin
dc.creatorVahdat, Amin
dc.date2006-05-02
dc.date2006-07-29
dc.date.accessioned2026-07-07T09:32:45Z
dc.date.available2026-07-07T09:32:45Z
dc.descriptionWe present a new, systematic approach for analyzing network topologies. We first introduce the dK-series of probability distributions specifying all degree correlations within d-sized subgraphs of a given graph G. Increasing values of d capture progressively more properties of G at the cost of more complex representation of the probability distribution. Using this series, we can quantitatively measure the distance between two graphs and construct random graphs that accurately reproduce virtually all metrics proposed in the literature. The nature of the dK-series implies that it will also capture any future metrics that may be proposed. Using our approach, we construct graphs for d=0,1,2,3 and demonstrate that these graphs reproduce, with increasing accuracy, important properties of measured and modeled Internet topologies. We find that the d=2 case is sufficient for most practical purposes, while d=3 essentially reconstructs the Internet AS- and router-level topologies exactly. We hope that a systematic method to analyze and synthesize topologies offers a significant improvement to the set of tools available to network topology and protocol researchers.
dc.descriptionFinal version
dc.identifierhttps://arxiv.org/abs/cs/0605007
dc.identifierhttp://arxiv.org/abs/cs/0605007
dc.identifierSIGCOMM 2006 (ACM SIGCOMM Computer Communication Review (CCR), v.36, n.4, p.135-146, 2006)
dc.identifierdoi:10.1145/1151659.1159930
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/158893
dc.subjectNetworking and Internet Architecture
dc.subjectStatistical Mechanics
dc.subjectPhysics and Society
dc.subjectC.2.1; G.3; G.2.2
dc.titleSystematic Topology Analysis and Generation Using Degree Correlations
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