Degree Distribution of Competition-Induced Preferential Attachment Graphs

dc.creatorBerger, N.
dc.creatorBorgs, C.
dc.creatorChayes, J. T.
dc.creatorD'Souza, R. M.
dc.creatorKleinberg, R. D.
dc.date2005-02-08
dc.date2005-02-08
dc.date.accessioned2026-07-07T03:03:39Z
dc.date.available2026-07-07T03:03:39Z
dc.descriptionWe introduce a family of one-dimensional geometric growth models, constructed iteratively by locally optimizing the tradeoffs between two competing metrics, and show that this family is equivalent to a family of preferential attachment random graph models with upper cutoffs. This is the first explanation of how preferential attachment can arise from a more basic underlying mechanism of local competition. We rigorously determine the degree distribution for the family of random graph models, showing that it obeys a power law up to a finite threshold and decays exponentially above this threshold. We also rigorously analyze a generalized version of our graph process, with two natural parameters, one corresponding to the cutoff and the other a ``fertility'' parameter. We prove that the general model has a power-law degree distribution up to a cutoff, and establish monotonicity of the power as a function of the two parameters. Limiting cases of the general model include the standard preferential attachment model without cutoff and the uniform attachment model.
dc.description24 pages, one figure. To appear in the journal: Combinatorics, Probability and Computing. Note, this is a long version, with complete proofs, of the paper "Competition-Induced Preferential Attachment" (cond-mat/0402268)
dc.identifierhttps://arxiv.org/abs/cond-mat/0502205
dc.identifierhttp://arxiv.org/abs/cond-mat/0502205
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/25830
dc.subjectDisordered Systems and Neural Networks
dc.subjectStatistical Mechanics
dc.subjectNetworking and Internet Architecture
dc.subjectProbability
dc.titleDegree Distribution of Competition-Induced Preferential Attachment Graphs
dc.typetext

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