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Target control of complex networks

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2014

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Nature Pub. Group
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Gao, Jianxi, Yang-Yu Liu, Raissa M. D'Souza, and Albert-László Barabási. 2014. “Target control of complex networks.” Nature Communications 5 (1): 5415. doi:10.1038/ncomms6415. http://dx.doi.org/10.1038/ncomms6415.

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Abstract

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.

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Target control of complex networks… : DASH Story 2015-12-17
This paper was helpful in understanding forward-looking applications that use graphs. It's important that government funded research is made accessible to the public. For me it provides insight and inspiration in STEM field. It also provides a view into how research starts to become commercialized, a critical step that is often hidden from the general public.