Abstract

We 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.

Original languageEnglish (US)
Article number066128
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume72
Issue number6
DOIs
StatePublished - Dec 1 2005

Fingerprint

Weighted Networks
Betweenness
Centrality
Complex Networks
Local Search Algorithm
Scale-free Networks
Vertex of a graph
Trade-offs
Class

All Science Journal Classification (ASJC) codes

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Condensed Matter Physics

Cite this

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title = "Search in weighted complex networks",
abstract = "We 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.",
author = "Thadakamalla, {Hari P.} and R. Albert and Kumara, {S. R.T.}",
year = "2005",
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language = "English (US)",
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journal = "Physical Review E",
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publisher = "American Physical Society",
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Search in weighted complex networks. / Thadakamalla, Hari P.; Albert, R.; Kumara, S. R.T.

In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, Vol. 72, No. 6, 066128, 01.12.2005.

Research output: Contribution to journalArticle

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