Acceleratingly growing scale-free networks with tunable degree exponents

作者：Yuan, Wu Jie^*; Luo, Xiao Shu; Zhou, Jian Fang; Wang, Bing Hong

来源：Physica A: Statistical Mechanics and Its Applications , 2008, 387(21): 5311-5316.

DOI：10.1016/j.physa.2008.04.033

• scale-free networks
• acceleratingly growing networks
• power-law degree distribution

In this paper, we analytically study the probabilistic accelerating network [M.J. Gagen, J.S. Mattick, Phys. Rev. E 72 (2005) 0161231 in its accelerating regimes by using mean field theory. In the growing network, the number of links added with each new node is a nonlinearly increasing function aN(beta)(t) where N(t) is the number of nodes present at time t. It is found that the network appears to have a power-law degree distribution for large degree with tunable degree exponents (ranging from 3.0 to theoretically infinity) and the degree exponent gamma depends only on the parameter beta as gamma = 1 + 2/1-beta. The analytical results are found to be in good agreement with those obtained by extensive numerical simulations.

• 出版日期2008-9-1
• 单位中国科学技术大学; 南宁师范大学; 广西师范大学