We propose a model for growing fractal networks based on the mechanisms learned from the diffusion-limited aggregation (DLA) model in fractal geometries in the viewpoint of network. By studying the DLA network, our model introduces multiplicative growth, aging and geographical preferential attachment mechanisms, whereby featuring topological self-similar property and hierarchical modularity. According to the results of theoretical analysis and simulation, the degree distribution of the proposed model shows a mixed degree distribution (i.e., exponential and algebraic degree distribution) and the fractal dimension and clustering coefficient can be tuned by changing the values of parameters.
Scopus Subject Areas
- Physics and Astronomy(all)