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)‡
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
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.
Accepted manuscript online:
PACS:
89.75.-k
(Complex systems)
Fund: 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
Cite this article:
Zhao Jing(赵静), Tao Lin(陶林), Yu Hong(俞鸿), Luo Jian-Hua(骆建华), Cao Zhi-Wei(曹志伟), and Li Yi-Xue(李亦学) The effects of degree correlations on network topologies and robustness 2007 Chinese Physics 16 3571
Characteristics of vapor based on complex networks in China Ai-Xia Feng(冯爱霞), Qi-Guang Wang(王启光), Shi-Xuan Zhang(张世轩), Takeshi Enomoto(榎本刚), Zhi-Qiang Gong(龚志强), Ying-Ying Hu(胡莹莹), and Guo-Lin Feng(封国林). Chin. Phys. B, 2022, 31(4): 049201.
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