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A method of characterizing network topology based on the breadth-first search tree

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Listed:
  • Zhou, Bin
  • He, Zhe
  • Wang, Nianxin
  • Wang, Bing-Hong

Abstract

A method based on the breadth-first search tree is proposed in this paper to characterize the hierarchical structure of network. In this method, a similarity coefficient is defined to quantitatively distinguish networks, and quantitatively measure the topology stability of the network generated by a model. The applications of the method are discussed in ER random network, WS small-world network and BA scale-free network. The method will be helpful for deeply describing network topology and provide a starting point for researching the topology similarity and isomorphism of networks.

Suggested Citation

  • Zhou, Bin & He, Zhe & Wang, Nianxin & Wang, Bing-Hong, 2016. "A method of characterizing network topology based on the breadth-first search tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 682-686.
    • Handle: RePEc:eee:phsmap:v:450:y:2016:i:c:p:682-686
    DOI: 10.1016/j.physa.2015.12.160
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    1. Chiara Orsini & Marija M. Dankulov & Pol Colomer-de-Simón & Almerima Jamakovic & Priya Mahadevan & Amin Vahdat & Kevin E. Bassler & Zoltán Toroczkai & Marián Boguñá & Guido Caldarelli & Santo Fortunat, 2015. "Quantifying randomness in real networks," Nature Communications, Nature, vol. 6(1), pages 1-10, December.
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    4. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 1999. "Mean-field theory for scale-free random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 272(1), pages 173-187.
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    Cited by:

    1. Wang, Yaran & Shi, Kaiyu & Zheng, Xuejing & You, Shijun & Zhang, Huan & Zhu, Chengzhi & Li, Liang & Wei, Shen & Ding, Chao & Wang, Na, 2020. "Thermo-hydraulic coupled analysis of meshed district heating networks based on improved breadth first search method," Energy, Elsevier, vol. 205(C).

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