具有无尺度拓扑与小世界效应的Sierpinski网络

Sierpinski networks with scale-free topology and small-world effect

复杂网络是目前国内外研究的热点之一,而分形则被认为是上个世纪学术界的一个重要发现.根据Sierpinski垫这一著名的分形结构,构建了一类确定性网络,称为Sierpinski网络.提出了生成该网络的一个迭代算法,使抽象的网络构造变得具体而直观.研究发现该网络具有与许多现实网络相似的结构特性:幂律度分布、较高的集聚系数和较小的直径.

Complex networks have attracted much research interest from different subjects and fractal has been recognized as one of the most important discoveries in the last century. In this paper, according to the famous fractals of Sierpinski Gasket, deterministic networks, called Sierpinski networks, are constructed and an iterative algorithm to generate the networks is proposed. The presented algorithm can concretize the abstract construction of Sierpinski networks. These networks have the typical properties of the real-life systems ： power-law degree distribution, large clustering coefficient and small diameter