[1]陈世明,程运洪,邓兵.有向相依网络的可控性研究[J].智能系统学报,2018,13(04):602-609.[doi:10.11992/tis.201703020]
 CHEN Shiming,CHENG Yunhong,DENG Bing.Research on the controllability of directed interdependent networks[J].CAAI Transactions on Intelligent Systems,2018,13(04):602-609.[doi:10.11992/tis.201703020]
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有向相依网络的可控性研究(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第13卷
期数:
2018年04期
页码:
602-609
栏目:
出版日期:
2018-07-05

文章信息/Info

Title:
Research on the controllability of directed interdependent networks
作者:
陈世明 程运洪 邓兵
华东交通大学 电气与自动化工程学院, 江西 南昌 330013
Author(s):
CHEN Shiming CHENG Yunhong DENG Bing
School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China
关键词:
有向网络相依网络相依方式严格可控性
Keywords:
directed networkinterdependent networkinterdependencyexact controllability
分类号:
TP273;N941
DOI:
10.11992/tis.201703020
摘要:
针对相依方式对有向相依网络可控性的影响,研究了不同相依方式下有向相依网络的可控性。通过构建基本的有向相依网络模型,结合严格可控性理论,给出了可控性评判指标。同时基于经典的有向随机网络和有向无标度网络,提出3种有向相依网络模型,并研究了随机相依条件下有向相依网络的可控性。随后定义了3种相依方式,并对比分析了在不同相依方式下有向相依网络的可控性。结果表明,在同等相依比例下,基于最低入度与最低出度节点相依的有向相依网络可控性最强,而基于最高入度与最高出度节点相依的有向相依网络可控性最弱,研究成果能够为实际有向相依网络的构建提供有益的参考和指导。
Abstract:
In this paper, we consider the influence of interdependency on the controllability of interdependent directed networks and investigate the controllability of interdependent directed networks with different types of interdependency. We build a basic interdependent directed network model and generate a controllability index by introducing the theory of exact controllability. We propose three kinds of interdependent directed network models for classical directed random networks and directed scale-free networks. In addition, we investigate the controllability of the interdependent directed networks with random interdependencies. Based on the results, we propose three kinds of interdependencies and compare and analyze the controllability of interdependent directed networks with different types of interdependency. The results show that, with the same proportion of interdependence, the best controllability of an interdependent directed network is that with an interdependency of lowest in-degree and lowest out-degree nodes, whereas the poorest controllability of an interdependent directed network is that with an interdependency of highest in-degree and highest out-degree nodes. The research results provide a useful reference and guidance for the construction of actual interdependent directed networks.

参考文献/References:

[1] MORENO Y, NEKOVEE M, PACHECO A F. Dynamics of rumor spreading in complex networks[J]. Physical review E, 2004, 69(6):066130.
[2] NEWMAN M E, GIRVAN M. Finding and evaluating community structure in networks[J]. Physical review E, 2004, 69(2):026113.
[3] SHEN J, ZHENG B. Cross-correlation in financial dynamics[J]. Europhysics letters, 2009, 86(4):48005.
[4] LIN Chingtai. Structural controllability[J]. IEEE transactions on automatic control, 1974, 19(3):201-208.
[5] LIU Yangyu, SLOTINE J J, BARABÁSI A L. Controllability of complex networks[J]. Nature, 2011, 473(7346):167-173.
[6] JIA Tao, LIU Yangyu, CSÓKA E, et al. Emergence of bimodality in controlling complex networks[J]. Nature communications, 2013, 4:2002.
[7] JIA Tao, BARABÁSI A L. Control capacity and a random sampling method in exploring controllability of complex networks[J]. Scientific reports, 2013, 3:2354.
[8] WANG Wenxu, NI Xuan, LAI Yingcheng, et al. Optimizing controllability of complex networks by minimum structural perturbations[J]. Physical review E, 2012, 85(2):026115.
[9] XU Jiuqiang, WANG Jinfang, ZHAO Hai, et al. Improving controllability of complex networks by rewiring links regularly[C]//Proceedings of the 26th Chinese Control and Decision Conference. Changsha, China:IEEE, 2014:642-645.
[10] HOU Lvlin, LAO Songyang, SMALL M, et al. Enhancing complex network controllability by minimum link direction reversal[J]. Physics letters A, 2015, 379(20/21):1321-1325.
[11] YUAN Zhengzhong, ZHAO Chen, DI Zengru, et al. Exact controllability of complex networks[J]. Nature communications, 2013, 4:2447.
[12] LI Jingwen, YUAN Zhengzhong, FAN Ying, et al. Controllability of fractal networks:an analytical approach[J]. Europhysics letters, 2014, 105(5):58001.
[13] BULDYREV S V, PARSHANI R, PAUL G, et al. Catastrophic cascade of failures in interdependent networks[J]. Nature, 2010, 464(7291):1025-1028.
[14] WANG Jianwei, LI Yun, ZHENG Qiaofang. Cascading load model in interdependent networks with coupled strength[J]. Physica A:statistical mechanics and its applications, 2015, 430:242-253.
[15] WANG Jianwei, JIANG Chen, QIAN Jianfei. Robustness of interdependent networks with different link patterns against cascading failures[J]. Physica A:statistical mechanics and its applications, 2014, 393:535-541.
[16] CHENG Zunshui, CAO Jinde. Cascade of failures in interdependent networks coupled by different type networks[J]. Physica A:statistical mechanics and its applications, 2015, 430:193-200.
[17] 陈世明, 吕辉, 徐青刚, 等. 基于度的正/负相关相依网络模型及其鲁棒性研究[J]. 物理学报, 2015, 64(4):048902. CHEN Shiming, LÜ Hui, XU Qinggang, et al. The model of interdependent network based on positive/negative correlation of the degree and its robustness study[J]. Acta physica sinica, 2015, 64(4):048902.
[18] GÓMEZ S, DÍAZ-GUILERA A, GÓMEZ-GARDEÑES J, et al. Diffusion dynamics on multiplex networks[J]. Physical review letters, 2013, 110(2):028701.
[19] OHTSUKI H, NOWAK M A, PACHECO J M. Breaking the symmetry between interaction and replacement in evolutionary dynamics on graphs[J]. Physical review letters, 2007, 98(10):108106.
[20] BARRETO E, HUNT B, OTT E, et al. Synchronization in networks of networks:the onset of coherent collective behavior in systems of interacting populations of heterogeneous oscillators[J]. Physical review E, 2007, 77(3):036107.
[21] YUAN Zhengzhong, ZHAO Chen, WANG Wenxu, et al. Exact controllability of multiplex networks[J]. New journal of physics, 2014, 16(10):103036.
[22] NIE Sen, WANG Xuwen, WANG Binghong. Effect of degree correlation on exact controllability of multiplex networks[J]. Physica A:statistical mechanics and its applications, 2015, 436:98-102.

备注/Memo

备注/Memo:
收稿日期:2017-03-15。
基金项目:国家自然科学基金项目(61364017).
作者简介:陈世明,男,1977年生,教授,博士生导师,主要研究方向为群体动力学与协调控制、复杂网络理论及应用、多机器人系统、粒子群优化算法。先后主持国家自然科学基金项目3项、其他省部级项目10余项,发表学术论文70余篇,其中SCI、EI检索近50篇;程运洪,男,1991年生,硕士研究生,主要研究方向为相依网络的鲁棒性优化研究;邓兵,男,1991年生,硕士研究生,主要研究方向相依网络级联失效的可控性研究。
通讯作者:陈世明.E-mail:shmchen@ecjtu.jx.cn.
更新日期/Last Update: 2018-08-25