Inhomogeneous substructures hidden in random networks

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dc.contributor.authorKim D.-H.ko
dc.contributor.authorJeong, Hawoongko
dc.date.accessioned2007-11-05T06:02:51Z-
dc.date.available2007-11-05T06:02:51Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2006-
dc.identifier.citationPHYSICAL REVIEW E, v.73, no.3, pp.1 - 4-
dc.identifier.issn1539-3755-
dc.identifier.urihttp://hdl.handle.net/10203/1811-
dc.description.abstractWe study the structure of the load-based spanning tree (LST) that carries the maximum weight of the Erdos-Renyi (ER) random network. The weight of an edge is given by the edge-betweenness centrality, the effective number of shortest paths through the edge. We find that the LSTs present very inhomogeneous structures in contrast to the homogeneous structures of the original networks. Moreover, it turns out that the structure of the LST changes dramatically as the edge density of an ER network increases, from scale free with a cutoff, scale free, to a starlike topology. These would not be possible if the weights are randomly distributed, which implies that topology of the shortest path is correlated in spite of the homogeneous topology of the random network.-
dc.description.sponsorshipThis work was supported by Grant No. R14-2002-059-01002-0 from the KOSEF-ABRL Program (D.H.K.) and by Grant No. R01-2005-000-1112-0 from the Basic Research Program of the Korea Science and Engineering Foundation (H.J.)en
dc.languageEnglish-
dc.language.isoen_USen
dc.publisherAMER PHYSICAL SOC-
dc.subjectCOMPLEX NETWORKS-
dc.subjectINTERNET-
dc.subjectCENTRALITY-
dc.titleInhomogeneous substructures hidden in random networks-
dc.typeArticle-
dc.identifier.wosid000236467700120-
dc.identifier.scopusid2-s2.0-33644927279-
dc.type.rimsART-
dc.citation.volume73-
dc.citation.issue3-
dc.citation.beginningpage1-
dc.citation.endingpage4-
dc.citation.publicationnamePHYSICAL REVIEW E-
dc.identifier.doi10.1103/PhysRevE.73.037102-
dc.contributor.localauthorJeong, Hawoong-
dc.contributor.nonIdAuthorKim D.-H.-
dc.type.journalArticleArticle-
dc.subject.keywordPlusCOMPLEX NETWORKS-
dc.subject.keywordPlusINTERNET-
dc.subject.keywordPlusCENTRALITY-
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