Search in weighted complex networks

dc.creatorThadakamalla, Hari P.
dc.creatorAlbert, Reka
dc.creatorKumara, Soundar R. T.
dc.date2005-11-18
dc.date2006-01-20
dc.date.accessioned2026-07-07T06:49:18Z
dc.date.available2026-07-07T06:49:18Z
dc.descriptionWe study trade-offs presented by local search algorithms in complex networks which are heterogeneous in edge weights and node degree. We show that search based on a network measure, local betweenness centrality (LBC), utilizes the heterogeneity of both node degrees and edge weights to perform the best in scale-free weighted networks. The search based on LBC is universal and performs well in a large class of complex networks.
dc.description14 pages, 5 figures, 4 tables, minor changes, added a reference
dc.identifierhttps://arxiv.org/abs/cond-mat/0511476
dc.identifierhttp://arxiv.org/abs/cond-mat/0511476
dc.identifierPhys. Rev. E 72, 066128 (2005)
dc.identifierdoi:10.1103/PhysRevE.72.066128
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/104290
dc.subjectStatistical Mechanics
dc.subjectDisordered Systems and Neural Networks
dc.titleSearch in weighted complex networks
dc.typetext

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