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Jamming in complex gradient networks.

Kwangho Park1, Ying-Cheng Lai, Liang Zhao

  • 1Department of Electrical Engineering, Arizona State University, Tempe, Arizona 85287, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|August 11, 2005
PubMed
Summary
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Jamming in complex networks, like those in nature or technology, depends on network structure. Scale-free networks show more congestion than random networks below a critical connectivity, but less above it.

Area of Science:

  • Network Science
  • Physics of Complex Systems
  • Statistical Mechanics

Background:

  • Flows of physical quantities in complex networks depend on scalar gradients.
  • Understanding congestion and jamming is crucial for network function.

Purpose of the Study:

  • Investigate conditions for jamming in gradient flows.
  • Compare jamming in random and scale-free networks.

Main Methods:

  • Analytical investigation of gradient flows.
  • Numerical simulations on network models.

Main Results:

  • Jamming degree generally increases with average connectivity ().
  • A crossover phenomenon in congestion is observed at critical connectivity (k(c) ≈ 10).

Related Experiment Videos

  • Scale-free networks exhibit higher congestion than random networks for < k(c), and vice versa for > k(c).

    • Conclusions:

    • Network topology significantly impacts gradient flow congestion.
    • The critical connectivity distinguishes behavior between random and scale-free networks.