Impact of community structure on information transfer

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 that 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.

6 pages, 5 figures, 1 table, figures, text and references updated

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Cited by in corpus (9)

• Random walks and diffusion on networks
• Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics
• Designing optimal transport networks
• The Large Scale Curvature of Networks
• Collectively optimal routing for congested traffic limited by link capacity
• Perturbation centrality and Turbine: a novel centrality measure obtained using a versatile network dynamics tool
• Controlling congestion on complex networks: fairness, efficiency and network structure
• Network modules help the identification of key transport routes, signaling pathways in cellular and other networks
• The role of hidden influentials in the diffusion of online information cascades