Literature DB >> 18517457

Impact of community structure on information transfer.

Leon Danon1, Alex Arenas, Albert Díaz-Guilera.   

Abstract

The observation that real complex networks have internal structure has important implication for dynamic processes occurring on such topologies. Here we investigate the impact of community structure on a model of information transfer able to deal with both search and congestion simultaneously. We show that networks with fuzzy community structure are more efficient in terms of packet delivery than those with pronounced community structure. We also propose an alternative packet routing algorithm which takes advantage of the knowledge of communities to improve information transfer and show that in the context of the model an intermediate level of community structure is optimal. Finally, we show that in a hierarchical network setting, providing knowledge of communities at the level of highest modularity will improve network capacity by the largest amount.

Year:  2008        PMID: 18517457     DOI: 10.1103/PhysRevE.77.036103

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  3 in total

1.  Perturbation centrality and turbine: a novel centrality measure obtained using a versatile network dynamics tool.

Authors:  Kristóf Z Szalay; Peter Csermely
Journal:  PLoS One       Date:  2013-10-21       Impact factor: 3.240

2.  Controlling congestion on complex networks: fairness, efficiency and network structure.

Authors:  Ľuboš Buzna; Rui Carvalho
Journal:  Sci Rep       Date:  2017-08-22       Impact factor: 4.379

3.  Noise enhances information transfer in hierarchical networks.

Authors:  Agnieszka Czaplicka; Janusz A Holyst; Peter M A Sloot
Journal:  Sci Rep       Date:  2013-02-06       Impact factor: 4.379

  3 in total

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