中国物理B ›› 2007, Vol. 16 ›› Issue (12): 3571-3580.doi: 10.1088/1009-1963/16/12/004

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The effects of degree correlations on network topologies and robustness

骆建华1, 赵 静2, 李亦学3, 陶 林4, 俞 鸿4, 曹志伟4   

  1. (1)School of Life Sciences & Technology, Shanghai Jiaotong University, Shanghai 200240, China; (2)School of Life Sciences & Technology, Shanghai Jiaotong University, Shanghai 200240, China;Shanghai Center for Bioinformation and Technology, Shanghai 200235, China;Department of Mathematics, Logistical Engineering University, Chongqing 400016, China; (3)School of Life Sciences & Technology, Shanghai Jiaotong University, Shanghai 200240, China;Shanghai Center for Bioinformation and Technology, Shanghai 200235, China;Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; (4)Shanghai Center for Bioinformation and Technology, Shanghai 200235, China
  • 出版日期:2007-12-20 发布日期:2007-12-20
  • 基金资助:
    Project supported by the Research Foundation from Ministry of Science and Technology, China (Grant Nos 2006AA02Z317, 2004CB720103, 2003CB715901 and 2006AA02312), the National High Technology Research and Development Program of China (Grant No 2006AA020805

The effects of degree correlations on network topologies and robustness

Zhao Jing(赵静)a)b)d), Tao Lin(陶林)b), Yu Hong(俞鸿)b), Luo Jian-Hua(骆建华)a), Cao Zhi-Wei(曹志伟)b)†, and Li Yi-Xue(李亦学)a)b)c)‡   

  1. a School of Life Sciences & Technology, Shanghai Jiaotong University, Shanghai 200240, China; b Shanghai Center for Bioinformation and Technology, Shanghai 200235, Chinac Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; d Department of Mathematics, Logistical Engineering University, Chongqing 400016, China
  • Online:2007-12-20 Published:2007-12-20
  • Supported by:
    Project supported by the Research Foundation from Ministry of Science and Technology, China (Grant Nos 2006AA02Z317, 2004CB720103, 2003CB715901 and 2006AA02312), the National High Technology Research and Development Program of China (Grant No 2006AA020805

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摘要： Complex networks have been applied to model numerous interactive nonlinear systems in the real world. Knowledge about network topology is crucial to an understanding of the function, performance and evolution of complex systems. In the last few years, many network metrics and models have been proposed to investigate the network topology, dynamics and evolution. Since these network metrics and models are derived from a wide range of studies, a systematic study is required to investigate the correlations among them. The present paper explores the effect of degree correlation on the other network metrics through studying an ensemble of graphs where the degree sequence (set of degrees) is fixed. We show that to some extent, the characteristic path length, clustering coefficient, modular extent and robustness of networks are directly influenced by the degree correlation.

关键词: network dynamics, random graphs, complex networks, degree correlation

Abstract: Complex networks have been applied to model numerous interactive nonlinear systems in the real world. Knowledge about network topology is crucial to an understanding of the function, performance and evolution of complex systems. In the last few years, many network metrics and models have been proposed to investigate the network topology, dynamics and evolution. Since these network metrics and models are derived from a wide range of studies, a systematic study is required to investigate the correlations among them. The present paper explores the effect of degree correlation on the other network metrics through studying an ensemble of graphs where the degree sequence (set of degrees) is fixed. We show that to some extent, the characteristic path length, clustering coefficient, modular extent and robustness of networks are directly influenced by the degree correlation.

Key words: network dynamics, random graphs, complex networks, degree correlation

中图分类号:  (Complex systems)

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