Complex Sciences. First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009. Revised Papers, Part 1

Research Article

On General Laws of Complex Networks

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  • @INPROCEEDINGS{10.1007/978-3-642-02466-5_10,
        author={Wenjun Xiao and Limin Peng and Behrooz Parhami},
        title={On General Laws of Complex Networks},
        proceedings={Complex Sciences. First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009. Revised Papers, Part 1},
        proceedings_a={COMPLEX PART 1},
        year={2012},
        month={5},
        keywords={complex network self-similarity scale-free computer network computer communication},
        doi={10.1007/978-3-642-02466-5_10}
    }
    
  • Wenjun Xiao
    Limin Peng
    Behrooz Parhami
    Year: 2012
    On General Laws of Complex Networks
    COMPLEX PART 1
    Springer
    DOI: 10.1007/978-3-642-02466-5_10
Wenjun Xiao1,*, Limin Peng1,*, Behrooz Parhami2,*
  • 1: South China University of Technology
  • 2: University of California
*Contact email: wjxiao@scut.edu.cn, penglm86@126.com, parhami@ece.ucsb.edu

Abstract

By introducing and analyzing a renormalization procedure, Song et al. [1] draw the conclusion that many complex networks exhibit self-repeating patterns on all length scales. First, we aim to demonstrate that the aforementioned conclusion is inadequately justified, mainly because their equation (7) on the invariance of degree distribution under renormalization does not hold in general. Secondly, Barabási and Albert [2] find that many large networks exhibit a scale-free power-law distribution of vertex degrees. They show this common feature to be a consequence of two generic mechanisms: (i) networks expand continuously by the addition of new vertices, and (ii) new vertices attach preferentially to those that are already well connected. We show that when vertex degrees of large networks follow a scale-free power-law distribution with the exponent  ≥ 2, the number of degree-1 vertices, when nonzero, is of the same order as the network size N and that the average degree is of order less than log N. Given that many real networks satisfy these two conditions, our results add another necessary characteristic of the scale-free power-law distribution of vertex degrees in such networks. Our method has the benefit of relying on conditions that are static and easily verified. They are verified by many experimental results of diverse real networks.