Self-Organization Induced Scale-Free Networks
Abstract
What is the underlying mechanism leading to power-law degree distributions of many natural and artificial networks is still at issue. We consider that scale-free networks emerges from self-organizing process, and such a evolving model is introduced in this letter. At each time step, a new node is added to the network and connect to some existing nodes randomly, instead of "preferential attachment" introduced by Barab\'{a}si and Albert, and then the new node will connect with its neighbors' neighbors at a fixed probability, which is natural to collaboration networks and social networks of acquaintance or other relations between individuals. The simulation results show that those networks generated from our model are scale-free networks with satisfactorily large clustering coefficient.
Cite
@article{arxiv.cond-mat/0408631,
title = {Self-Organization Induced Scale-Free Networks},
author = {Gang Yan and Tao Zhou and Ying-Di Jin and Zhong-Qian Fu},
journal= {arXiv preprint arXiv:cond-mat/0408631},
year = {2007}
}
Comments
9 eps figures, 4 pages