منابع مشابه
Degree distributions of growing networks.
The in-degree and out-degree distributions of a growing network model are determined. The in-degree is the number of incoming links to a given node (and vice versa for out-degree). The network is built by (i) creation of new nodes which each immediately attach to a preexisting node, and (ii) creation of new links between preexisting nodes. This process naturally generates correlated in-degree a...
متن کاملMarkovian iterative method for degree distributions of growing networks.
Currently, simulation is usually used to estimate network degree distribution P(k) and to examine if a network model predicts a scale-free network when an analytical formula does not exist. An alternative Markovian chain-based numerical method was proposed by Shi [Phys. Rev. E 71, 036140 (2005)] to compute time-dependent degree distribution P(k,t) . Although the numerical results demonstrate a ...
متن کاملDegree-Distribution Stability of Growing Networks
In this paper, we abstract a kind of stochastic processes from evolving processes of growing networks, this process is called growing network Markov chains. Thus the existence and the formulas of degree distribution are transformed to the corresponding problems of growing network Markov chains. First we investigate the growing network Markov chains, and obtain the condition in which the steady ...
متن کاملMarkov chain-based numerical method for degree distributions of growing networks.
In this paper, we establish a relation between growing networks and Markov chains, and propose a computational approach for network degree distributions. Using the Barabási-Albert model as an example, we first show that the degree evolution of a node in a growing network follows a nonhomogeneous Markov chain. Exploring the special structure of these Markov chains, we develop an efficient algori...
متن کاملTuning degree distributions of scale - free networks
We present an algorithm that generates networks in which the skewness of the degree distribution is tuneable by modifying the preferential attachment step of the Barabási-Albert construction algorithm. Skewness is linearly correlated with the maximal degree of the network and, therefore, adequately represents the influence of superspreaders or hubs. By combining our algorithm with work of Holme...
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ژورنال
عنوان ژورنال: Physical Review Letters
سال: 2001
ISSN: 0031-9007,1079-7114
DOI: 10.1103/physrevlett.86.5401