Recursive weighted treelike networks

Abstract

We propose a geometric growth model for weighted scale-free networks, which is controlled by two tunable parameters. We derive exactly the main characteristics of the networks, which are partially determined by the parameters. Analytical results indicate that the resulting networks have power-law distributions of degree, strength, weight and betweenness, a scale-free behavior for degree correlations, logarithmic small average path length and diameter with network size. The obtained properties are in agreement with empirical data observed in many real-life networks, which shows that the presented model may provide valuable insight into the real systems.

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Cited by in corpus (7)

• Topologies and Laplacian spectra of a deterministic uniform recursive tree
• Effects of accelerating growth on the evolution of weighted complex networks
• Recursive weighted treelike networks
• Influences of degree inhomogeneity on average path length and random walks in disassortative scale-free networks
• Structural and spectral properties of a family of deterministic recursive trees: Rigorous solutions
• Stochastic Weighted Fractal Networks
• Analytic Solution to Clustering Coefficients on Weighted Networks