"Winner takes it all": strongest node rule for evolution of scale free networks
arXiv:cond-mat/0409648 · doi:10.1103/PhysRevE.72.036105
Abstract
We study a novel model for evolution of complex networks. We introduce information filtering for reduction of the number of available nodes to a randomly chosen sample, as stochastic component of evolution. New nodes are attached to the nodes that have maximal degree in the sample, which is a deterministic component of network evolution process. This fact is a novel for evolution of scale free networks and depicts a possible new route for modeling network growth. We present both simulational and theoretical results for network evolution. The obtained degree distributions exhibit an obvious power-law behavior in the middle with the exponential cut off in the end. This highlights the essential characteristics of information filtering in the network growth mechanisms.
6 pages, 9 figures, revtex
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