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Crossover behavior in a communication network.

Brajendra K Singh1, Neelima Gupte

  • 1Department of Physics, Indian Institute of Technology, Madras, Chennai 600 036, India. braj@chaos.iitm.ernet.in

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|February 3, 2004
PubMed
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This study explores message transfer in lattice networks with hubs. Introducing assortative connections between hubs changes travel time distributions from fat-fractal to power-law behavior, impacting information spread.

Area of Science:

  • Network Science
  • Statistical Physics
  • Information Theory

Background:

  • Communication networks often exhibit complex topologies.
  • Understanding message transfer and information spread is crucial.
  • Lattice networks with hubs present unique structural properties.

Purpose of the Study:

  • To investigate message transfer dynamics in a 2D lattice network with hubs.
  • To analyze the impact of network topology modifications on information spread.
  • To characterize travel time distributions and disease transmission thresholds.

Main Methods:

  • Modeling a 2D lattice network with nearest-neighbor and hub connections.
  • Analyzing degree distribution, which is bimodal with finite variance.

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  • Investigating travel time distributions and disease spread under different network configurations.

    • Main Results:

    • Fat-fractal behavior in travel time distributions as a function of hub density.
    • Crossover to power-law behavior in travel time distributions with added assortative hub connections.
    • Milder crossover observed with end-to-end shortcuts between overlapping hub influence areas.
    • Crossover from one power law to another for disease transmission thresholds with assortative connections.

    Conclusions:

    • Network topology significantly influences information spread processes.
    • Assortative connections in hub-dominated networks can alter transmission dynamics.
    • The study provides insights into network behavior relevant to communication and epidemiology.