Literature DB >> 25170736

Network controllability is determined by the density of low in-degree and out-degree nodes.

Giulia Menichetti1, Luca Dall'Asta2, Ginestra Bianconi3.   

Abstract

The problem of controllability of the dynamical state of a network is central in network theory and has wide applications ranging from network medicine to financial markets. The driver nodes of the network are the nodes that can bring the network to the desired dynamical state if an external signal is applied to them. Using the framework of structural controllability, here, we show that the density of nodes with in degree and out degree equal to one and two determines the number of driver nodes in the network. Moreover, we show that random networks with minimum in degree and out degree greater than two, are always fully controllable by an infinitesimal fraction of driver nodes, regardless of the other properties of the degree distribution. Finally, based on these results, we propose an algorithm to improve the controllability of networks.

Mesh:

Year:  2014        PMID: 25170736     DOI: 10.1103/PhysRevLett.113.078701

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  23 in total

1.  Controllability of networked higher-dimensional systems with one-dimensional communication.

Authors:  Lin Wang; Xiaofan Wang; Guanrong Chen
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2017-03-06       Impact factor: 4.226

2.  Input graph: the hidden geometry in controlling complex networks.

Authors:  Xizhe Zhang; Tianyang Lv; Yuanyuan Pu
Journal:  Sci Rep       Date:  2016-11-30       Impact factor: 4.379

3.  Stochastic cycle selection in active flow networks.

Authors:  Francis G Woodhouse; Aden Forrow; Joanna B Fawcett; Jörn Dunkel
Journal:  Proc Natl Acad Sci U S A       Date:  2016-07-05       Impact factor: 11.205

4.  Harnessing tipping points in complex ecological networks.

Authors:  Junjie Jiang; Alan Hastings; Ying-Cheng Lai
Journal:  J R Soc Interface       Date:  2019-09-11       Impact factor: 4.118

5.  Multiplex congruence network of natural numbers.

Authors:  Xiao-Yong Yan; Wen-Xu Wang; Guan-Rong Chen; Ding-Hua Shi
Journal:  Sci Rep       Date:  2016-03-31       Impact factor: 4.379

6.  Noise Response Data Reveal Novel Controllability Gramian for Nonlinear Network Dynamics.

Authors:  Kenji Kashima
Journal:  Sci Rep       Date:  2016-06-06       Impact factor: 4.379

7.  Energy scaling and reduction in controlling complex networks.

Authors:  Yu-Zhong Chen; Le-Zhi Wang; Wen-Xu Wang; Ying-Cheng Lai
Journal:  R Soc Open Sci       Date:  2016-04-20       Impact factor: 2.963

8.  Effects of Edge Directions on the Structural Controllability of Complex Networks.

Authors:  Yandong Xiao; Songyang Lao; Lvlin Hou; Michael Small; Liang Bai
Journal:  PLoS One       Date:  2015-08-17       Impact factor: 3.240

9.  Effect of edge pruning on structural controllability and observability of complex networks.

Authors:  Simachew Abebe Mengiste; Ad Aertsen; Arvind Kumar
Journal:  Sci Rep       Date:  2015-12-17       Impact factor: 4.379

10.  A geometrical approach to control and controllability of nonlinear dynamical networks.

Authors:  Le-Zhi Wang; Ri-Qi Su; Zi-Gang Huang; Xiao Wang; Wen-Xu Wang; Celso Grebogi; Ying-Cheng Lai
Journal:  Nat Commun       Date:  2016-04-14       Impact factor: 14.919

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.