Universal framework for edge controllability of complex networks

Abstract Dynamical processes occurring on the edges in complex networks are relevant to a variety of real-world situations. Despite recent advances, a framework for edge controllability is still required for complex networks of arbitrary structure and interaction strength. Generalizing a previously...

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Autores principales:	Shao-Peng Pang, Wen-Xu Wang, Fei Hao, Ying-Cheng Lai
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/32c88d54e3654a238f6636e24c28f4dc
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spelling	oai:doaj.org-article:32c88d54e3654a238f6636e24c28f4dc2021-12-02T16:06:16ZUniversal framework for edge controllability of complex networks10.1038/s41598-017-04463-52045-2322https://doaj.org/article/32c88d54e3654a238f6636e24c28f4dc2017-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-04463-5https://doaj.org/toc/2045-2322Abstract Dynamical processes occurring on the edges in complex networks are relevant to a variety of real-world situations. Despite recent advances, a framework for edge controllability is still required for complex networks of arbitrary structure and interaction strength. Generalizing a previously introduced class of processes for edge dynamics, the switchboard dynamics, and exploit- ing the exact controllability theory, we develop a universal framework in which the controllability of any node is exclusively determined by its local weighted structure. This framework enables us to identify a unique set of critical nodes for control, to derive analytic formulas and articulate efficient algorithms to determine the exact upper and lower controllability bounds, and to evaluate strongly structural controllability of any given network. Applying our framework to a large number of model and real-world networks, we find that the interaction strength plays a more significant role in edge controllability than the network structure does, due to a vast range between the bounds determined mainly by the interaction strength. Moreover, transcriptional regulatory networks and electronic circuits are much more strongly structurally controllable (SSC) than other types of real-world networks, directed networks are more SSC than undirected networks, and sparse networks are typically more SSC than dense networks.Shao-Peng PangWen-Xu WangFei HaoYing-Cheng LaiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-12 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Shao-Peng Pang Wen-Xu Wang Fei Hao Ying-Cheng Lai Universal framework for edge controllability of complex networks
description	Abstract Dynamical processes occurring on the edges in complex networks are relevant to a variety of real-world situations. Despite recent advances, a framework for edge controllability is still required for complex networks of arbitrary structure and interaction strength. Generalizing a previously introduced class of processes for edge dynamics, the switchboard dynamics, and exploit- ing the exact controllability theory, we develop a universal framework in which the controllability of any node is exclusively determined by its local weighted structure. This framework enables us to identify a unique set of critical nodes for control, to derive analytic formulas and articulate efficient algorithms to determine the exact upper and lower controllability bounds, and to evaluate strongly structural controllability of any given network. Applying our framework to a large number of model and real-world networks, we find that the interaction strength plays a more significant role in edge controllability than the network structure does, due to a vast range between the bounds determined mainly by the interaction strength. Moreover, transcriptional regulatory networks and electronic circuits are much more strongly structurally controllable (SSC) than other types of real-world networks, directed networks are more SSC than undirected networks, and sparse networks are typically more SSC than dense networks.
format	article
author	Shao-Peng Pang Wen-Xu Wang Fei Hao Ying-Cheng Lai
author_facet	Shao-Peng Pang Wen-Xu Wang Fei Hao Ying-Cheng Lai
author_sort	Shao-Peng Pang
title	Universal framework for edge controllability of complex networks
title_short	Universal framework for edge controllability of complex networks
title_full	Universal framework for edge controllability of complex networks
title_fullStr	Universal framework for edge controllability of complex networks
title_full_unstemmed	Universal framework for edge controllability of complex networks
title_sort	universal framework for edge controllability of complex networks
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/32c88d54e3654a238f6636e24c28f4dc
work_keys_str_mv	AT shaopengpang universalframeworkforedgecontrollabilityofcomplexnetworks AT wenxuwang universalframeworkforedgecontrollabilityofcomplexnetworks AT feihao universalframeworkforedgecontrollabilityofcomplexnetworks AT yingchenglai universalframeworkforedgecontrollabilityofcomplexnetworks
_version_	1718385014409789440

Universal framework for edge controllability of complex networks

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