Universal framework for edge controllability of complex networks
Autor: | Fei Hao, Wen-Xu Wang, Shao Peng Pang, Ying-Cheng Lai |
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Jazyk: | angličtina |
Rok vydání: | 2017 |
Předmět: |
Class (set theory)
Mathematical optimization Multidisciplinary Computer science Node (networking) Science Structure (category theory) Interaction strength Complex network Topology 01 natural sciences Network controllability Article 010305 fluids & plasmas Controllability Range (mathematics) 0103 physical sciences Medicine Enhanced Data Rates for GSM Evolution 010306 general physics |
Zdroj: | Scientific Reports, Vol 7, Iss 1, Pp 1-12 (2017) Scientific Reports |
ISSN: | 2045-2322 |
Popis: | 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. |
Databáze: | OpenAIRE |
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