Rank-based model for weighted network with hierarchical organization and disassortative mixing |
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Authors: | L Tian D-N Shi |
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Institution: | (1) College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, P.R. China |
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Abstract: | In this paper, we study a rank-based model for weighted network. The evolution rule of the network is based on the ranking
of node strength, which couples the topological growth and the weight dynamics. Analytically and by simulations, we demonstrate
that the generated networks recover the scale-free distributions of degree and strength in the whole region of the growth
dynamics parameter (α>0). Moreover, this network evolution mechanism can also produce scale-free property of weight, which
adds deeper comprehension of the networks growth in the presence of incomplete information. We also characterize the clustering
and correlation properties of this class of networks. It is showed that at α=1 a structural phase transition occurs, and for
α>1 the generated network simultaneously exhibits hierarchical organization and disassortative degree correlation, which is
consistent with a wide range of biological networks. |
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Keywords: | PACS" target="_blank">PACS 89 75 -k Complex systems 89 75 Hc Networks and genealogical trees |
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