Growth and preferential attachments have been coined as the two fundamental mechanisms responsible for the scale-free feature in complex networks, as characterized by an algebraic degree distribution. There are situations, particularly in biological networks, where growth is absent or not important, yet some of these networks still exhibit the scale-free feature with a small degree exponent. Here we propose two classes of models to account for this phenomenon. We show analytically and numerically that, in the first model, a spectrum of algebraic degree distributions with a small exponent can be generated. The second model incorporates weights for nodes, and it is able to generate robust scale-free degree distribution with larger algebraic exponents. Our results imply that it is natural for a complex network to self-organize itself into a scale-free state without growth.
|Original language||English (US)|
|Journal||Physical Review E - Statistical, Nonlinear, and Soft Matter Physics|
|State||Published - Aug 1 2005|
ASJC Scopus subject areas
- Statistical and Nonlinear Physics
- Statistics and Probability
- Condensed Matter Physics