Maximal planar scale-free Sierpinski networks with small-world effect and power-law strength-degree correlation

Abstract

Many real networks share three generic properties: they are scale-free, display a small-world effect, and show a power-law strength-degree correlation. In this paper, we propose a type of deterministically growing networks called Sierpinski networks, which are induced by the famous Sierpinski fractals and constructed in a simple iterative way. We derive analytical expressions for degree distribution, strength distribution, clustering coefficient, and strength-degree correlation, which agree well with the characterizations of various real-life networks. Moreover, we show that the introduced Sierpinski networks are maximal planar graphs.

6 pages, 5 figures, accepted by EPL

References in corpus (2)

• Recursive graphs with small-world scale-free properties
• Self-similarity, small-world, scale-free scaling, disassortativity, and robustness in hierarchical lattices

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• Geometry and Dynamics for Hierarchical Regular Networks