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Mobile user forecast and power-law acceleration invariance of scale-free networks
Authors:Guo Jin-Li  Guo Zhao-Hua and Liu Xue-Jiao
Affiliation:Business School, University of Shanghai for Science and Technology, Shanghai 200093, China; College of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Abstract:This paper studies and predicts the number growth of China's mobile users by using the power-law regression. We find that the number growth of the mobile users follows a power law. Motivated by the data on the evolution of the mobile users, we consider scenarios of self-organization of accelerating growth networks into scale-free structures and propose a directed network model, in which the nodes grow following a power-law acceleration. The expressions for the transient and the stationary average degree distributions are obtained by using the Poisson process. This result shows that the model generates appropriate power-law connectivity distributions. Therefore, we find a power-law acceleration invariance of the scale-free networks. The numerical simulations of the models agree with the analytical results well.
Keywords:mobile user forecast  power-law accelerating growth  complex networks  scale-free networks
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