Heterogeneous network with distance dependent connectivity
arXiv:0802.1431 · doi:10.1140/epjb/e2008-00236-4
Abstract
We investigate a network model based on an infinite regular square lattice embedded in the Euclidean plane where the node connection probability is given by the geometrical distance of nodes. We show that the degree distribution in the basic model is sharply peaked around its mean value. Since the model was originally developed to mimic the social network of acquaintances, to broaden the degree distribution we propose its generalization. We show that when heterogeneity is introduced to the model, it is possible to obtain fat tails of the degree distribution. Meanwhile, the small-world phenomenon present in the basic model is not affected. To support our claims, both analytical and numerical results are obtained.
6 pages, 4 figures, minor clarifications and references added
References in corpus (16)
- Statistical mechanics of complex networks
- The structure and function of complex networks
- Evolution of networks
- Scale-free topology of e-mail networks
- Modeling the Internet's Large-Scale Topology
- Class of correlated random networks with hidden variables
- Analysis of a large-scale weighted network of one-to-one human communication
- Self-similarity of complex networks and hidden metric spaces
- Crossover from Scale-Free to Spatial Networks
- Structure of a large social network
- Small-worlds: How and why
- Modulated Scale-free Network in the Euclidean Space
- Evolving networks with disadvantaged long-range connections
- Physical realizability of small-world networks
- Weighted Scale-free Networks in Euclidean Space Using Local Selection Rule
- Distance-dependent connectivity: Yet Another Approach to the Small World Phenomenon