Growing scale-free networks with small-world behavior
نویسندگان
چکیده
منابع مشابه
Growing scale-free networks with small-world behavior.
In the context of growing networks, we introduce a simple dynamical model that unifies the generic features of real networks: scale-free distribution of degree and the small-world effect. While the average shortest path length increases logarithmically as in random networks, the clustering coefficient assumes a large value independent of system size. We derive analytical expressions for the clu...
متن کاملGrowing scale-free small-world networks with tunable assortative coefficient
In this paper, we propose a simple rule that generates scale-free small-world networks with tunable assortative coefficient. These networks are constructed by two-stage adding process for each new node. The model can reproduce scale-free degree distributions and small-world effect. The simulation results are consistent with the theoretical predictions approximately. Interestingly, we obtain the...
متن کاملScale-free networks with a large- to small-world transition
Recently there have been a tremendous interest in models of networks with a power-law distribution of degree— so called “scale-free networks.” It has been observed that such networks, normally, have extremely short pathlengths, scaling logarithmically or slower with system size. As en exotic and unintuitive example we propose a simple stochastic model capable of generating scale-free networks w...
متن کاملScale-free networks with self-growing weight
We present a novel type of weighted scale-free network model, in which the weight grows independently of the attachment of new nodes. The evolution of this network is thus determined not only by the preferential attachment of new nodes to existing nodes but also by self-growing weight of existing links based on a simple weight-driven rule. This model is analytically tractable, so that the vario...
متن کاملGrowing scale-free networks with tunable clustering.
We extend the standard scale-free network model to include a "triad formation step." We analyze the geometric properties of networks generated by this algorithm both analytically and by numerical calculations, and find that our model possesses the same characteristics as the standard scale-free networks such as the power-law degree distribution and the small average geodesic length, but with th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Physical Review E
سال: 2002
ISSN: 1063-651X,1095-3787
DOI: 10.1103/physreve.65.057102