Please wait a minute...
Chinese Physics, 2007, Vol. 16(6): 1576-1580    DOI: 10.1088/1009-1963/16/6/014
GENERAL Prev   Next  

Normalized entropy of rank distribution: a novel measure of heterogeneity of complex networks

Wu Jun(吴俊), Tan Yue-Jin(谭跃进), Deng Hong-Zhong(邓宏钟), and Zhu Da-Zhi(朱大智)
College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China
Abstract  Many unique properties of complex networks result from heterogeneity. The measure and analysis of heterogeneity are important and desirable to the research of the properties and functions of complex networks. In this paper, the rank distribution is proposed as a new statistic feature of complex networks. Based on the rank distribution, a novel measure of the heterogeneity called a normalized entropy of rank distribution (NERD) is proposed. The NERD accords with the normal meaning of heterogeneity within the context of complex networks compared with conventional measures. The heterogeneity of scale-free networks is studied using the NERD. It is shown that scale-free networks become more heterogeneous as the scaling exponent decreases and the NERD of scale-free networks is independent of the number of vertices, which indicates that the NERD is a suitable and effective measure of heterogeneity for networks with different sizes.
Keywords:  complex networks      heterogeneity      rank distribution      scale-free networks  
Received:  28 September 2006      Revised:  14 November 2006      Accepted manuscript online: 
PACS:  05.70.Ce (Thermodynamic functions and equations of state)  
  02.50.Ng (Distribution theory and Monte Carlo studies)  
  05.40.-a (Fluctuation phenomena, random processes, noise, and Brownian motion)  
  89.75.Hc (Networks and genealogical trees)  
Fund: Project supported by the National Natural Science Foundation of China (Grant No 70501032).

Cite this article: 

Wu Jun(吴俊), Tan Yue-Jin(谭跃进), Deng Hong-Zhong(邓宏钟), and Zhu Da-Zhi(朱大智) Normalized entropy of rank distribution: a novel measure of heterogeneity of complex networks 2007 Chinese Physics 16 1576

[1] Analysis of cut vertex in the control of complex networks
Jie Zhou(周洁), Cheng Yuan(袁诚), Zu-Yu Qian(钱祖燏), Bing-Hong Wang(汪秉宏), and Sen Nie(聂森). Chin. Phys. B, 2023, 32(2): 028902.
[2] Vertex centrality of complex networks based on joint nonnegative matrix factorization and graph embedding
Pengli Lu(卢鹏丽) and Wei Chen(陈玮). Chin. Phys. B, 2023, 32(1): 018903.
[3] 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.
[4] Robust H state estimation for a class of complex networks with dynamic event-triggered scheme against hybrid attacks
Yahan Deng(邓雅瀚), Zhongkai Mo(莫中凯), and Hongqian Lu(陆宏谦). Chin. Phys. B, 2022, 31(2): 020503.
[5] Finite-time synchronization of uncertain fractional-order multi-weighted complex networks with external disturbances via adaptive quantized control
Hongwei Zhang(张红伟), Ran Cheng(程然), and Dawei Ding(丁大为). Chin. Phys. B, 2022, 31(10): 100504.
[6] LCH: A local clustering H-index centrality measure for identifying and ranking influential nodes in complex networks
Gui-Qiong Xu(徐桂琼), Lei Meng(孟蕾), Deng-Qin Tu(涂登琴), and Ping-Le Yang(杨平乐). Chin. Phys. B, 2021, 30(8): 088901.
[7] Complex network perspective on modelling chaotic systems via machine learning
Tong-Feng Weng(翁同峰), Xin-Xin Cao(曹欣欣), and Hui-Jie Yang(杨会杰). Chin. Phys. B, 2021, 30(6): 060506.
[8] Unpinning the spiral waves by using parameter waves
Lu Peng(彭璐) and Jun Tang(唐军). Chin. Phys. B, 2021, 30(5): 058202.
[9] Exploring individuals' effective preventive measures against epidemics through reinforcement learning
Ya-Peng Cui(崔亚鹏), Shun-Jiang Ni (倪顺江), and Shi-Fei Shen(申世飞). Chin. Phys. B, 2021, 30(4): 048901.
[10] Dynamic crossover in [VIO2+][Tf2N-]2 ionic liquid
Gan Ren(任淦). Chin. Phys. B, 2021, 30(1): 016105.
[11] Finite density scaling laws of condensation phase transition in zero-range processes on scale-free networks
Guifeng Su(苏桂锋), Xiaowen Li(李晓温), Xiaobing Zhang(张小兵), Yi Zhang(张一). Chin. Phys. B, 2020, 29(8): 088904.
[12] Effects of water on the structure and transport properties of room temperature ionic liquids and concentrated electrolyte solutions
Jinbing Zhang(张晋兵), Qiang Wang(王强), Zexian Cao(曹则贤). Chin. Phys. B, 2020, 29(8): 087804.
[13] Influential nodes identification in complex networks based on global and local information
Yuan-Zhi Yang(杨远志), Min Hu(胡敏), Tai-Yu Huang(黄泰愚). Chin. Phys. B, 2020, 29(8): 088903.
[14] Identifying influential spreaders in complex networks based on entropy weight method and gravity law
Xiao-Li Yan(闫小丽), Ya-Peng Cui(崔亚鹏), Shun-Jiang Ni(倪顺江). Chin. Phys. B, 2020, 29(4): 048902.
[15] Revealing the inhomogeneous surface chemistry on the spherical layered oxide polycrystalline cathode particles
Zhi-Sen Jiang(蒋之森), Shao-Feng Li(李少锋), Zheng-Rui Xu(许正瑞), Dennis Nordlund, Hendrik Ohldag, Piero Pianetta, Jun-Sik Lee, Feng Lin(林锋), Yi-Jin Liu(刘宜晋). Chin. Phys. B, 2020, 29(2): 026103.
No Suggested Reading articles found!