Network evolution by nonlinear preferential rewiring of edges

被引:11
作者
Xu, Xin-Jian [1 ,2 ]
Hu, Xiao-Ming [1 ]
Zhang, Li-Jie [3 ,4 ]
机构
[1] Shanghai Univ, Dept Math, Coll Sci, Shanghai 200444, Peoples R China
[2] Shanghai Univ, Inst Syst Sci, Shanghai 200444, Peoples R China
[3] Shanghai Univ, Dept Phys, Coll Sci, Shanghai 200444, Peoples R China
[4] Shanghai Key Lab Astrophys, Shanghai 200234, Peoples R China
关键词
Complex networks; Rewiring networks; STATISTICAL-MECHANICS; COMPLEX NETWORKS;
D O I
10.1016/j.physa.2011.02.032
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The mathematical framework for small-world networks proposed in a seminal paper by Watts and Strogatz sparked a widespread interest in modeling complex networks in the past decade. However, most of research contributing to static models is in contrast to real-world dynamic networks, such as social and biological networks, which are characterized by rearrangements of connections among agents. In this paper, we study dynamic networks evolved by nonlinear preferential rewiring of edges. The total numbers of vertices and edges of the network are conserved, but edges are continuously rewired according to the nonlinear preference. Assuming power-law kernels with exponents alpha and beta. the network structures in stationary states display a distinct behavior, depending only on beta. For beta > 1, the network is highly heterogeneous with the emergence of starlike structures. For beta < 1, the network is widely homogeneous with a typical connectivity. At beta = 1, the network is scale free with an exponential cutoff. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:2429 / 2434
页数:6
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