Distances in random graphs with finite variance degrees

dc.creatorvan der Hofstad, Remco
dc.creatorHooghiemstra, Gerard
dc.creatorVan Mieghem, Piet
dc.date2004-07-07
dc.date.accessioned2026-07-07T05:10:00Z
dc.date.available2026-07-07T05:10:00Z
dc.descriptionIn this paper we study a random graph with $N$ nodes, where node $j$ has degree $D_j$ and $\{D_j\}_{j=1}^N$ are i.i.d. with $\prob(D_j\leq x)=F(x)$. We assume that $1-F(x)\leq c x^{-τ+1}$ for some $τ>3$ and some constant $c>0$. This graph model is a variant of the so-called configuration model, and includes heavy tail degrees with finite variance. The minimal number of edges between two arbitrary connected nodes, also known as the graph distance or the hopcount, is investigated when $N\to \infty$. We prove that the graph distance grows like $\log_νN$, when the base of the logarithm equals $ν=\expec[D_j(D_j -1)]/\expec[D_j]>1$. This confirms the heuristic argument of Newman, Strogatz and Watts \cite{NSW00}. In addition, the random fluctuations around this asymptotic mean $\log_ν{N}$ are characterized and shown to be uniformly bounded. In particular, we show convergence in distribution of the centered graph distance along exponentially growing subsequences.
dc.description40 pages, 2 figures
dc.identifierhttps://arxiv.org/abs/math/0407092
dc.identifierhttp://arxiv.org/abs/math/0407092
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/71795
dc.subjectProbability
dc.subjectCombinatorics
dc.titleDistances in random graphs with finite variance degrees
dc.typetext

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