Target control of complex networks

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.


More publications
Barabasi, A.-L.

Science 343: 6169 (2014)

H. Shen, D. Wang, C. Song, A.-L. Barabási

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence , 291-297 (2014)

X. Z. Zhou, J. Menche, A.-L. Barabási, A. Sharma

Nature Communications 5:4212, 1-10 (2014)