Target control of complex networks

By Jianxi Gao, Yang-Yu Liu, Raissa M. D’Souza, Albert-László Barabási. Nature Communications, 2014

412 citations recorded by the source corpus.

Controlling large natural and technological networks is an outstanding challenge. It is typically neither feasible nor necessary to control the entire network, prompting us to explore target control: the efficient control of a preselected subset of nodes. We show that the structural controllability approach used for full control overestimates the minimum number of driver nodes needed for target control. Here we develop an alternate ‘k-walk’ theory for directed tree networks, and we rigorously prove that one node can control a set of target nodes if the path length to each target node is unique. For more general cases, we develop a greedy algorithm to approximate the minimum set of driver nodes sufficient for target control. We find that degree heterogeneous networks are target controllable with higher efficiency than homogeneous networks and that the structure of many real-world networks are suitable for efficient target control. Network controllability has numerous applications in natural and technological systems. Here, Gao et al.develop a theoretical approach and a greedy algorithm to study target control—the ability to efficiently control a preselected subset of nodes—in complex networks.

Subfields: Computer Networks and Communications, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/712c1a44dbe91ad5a7a973283cf14ef291b480f9

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In Computer Networks and Communications

In Statistical and Nonlinear Physics

Citations in the corpus

Dimensionality in recurrent spiking networks: Global trends in activity and local origins in connectivity (2018, background): “The same argument holds true for the way internal activity in a recurrent 468 network is generated intrinsically in a network, as some neurons, and their connectivity 469 patterns, are known to have a stronger influence [61, 62].”
Control Principles of Complex Networks (2015, background): “New notions, from multiplex networks (Boccaletti 55 et al., 2014; Kivel et al., 2014) to networks of networks (D’Agostino and Scala, 2014; Gao et al., 2014a), have been recently proposed to explore the properties of these systems, focusing mainly on their structural integrity and robustness.”
Network resilience (2020, background): “the study of controllability attracts much attention towards the control of complex networks [756, 757, 758].”