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Target control of complex networks

  • Northeastern University
  • Dana-Farber Cancer Institute
  • Brigham and Women’s Hospital
  • University of California at Davis
  • Santa Fe Institute
  • Harvard Medical School, Boston

Research output: Contribution to journalArticlepeer-review

Abstract (may include machine translation)

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.

Original languageEnglish
Article number5415
Number of pages8
JournalNature Communications
Volume5
DOIs
StatePublished - 12 Nov 2014
Externally publishedYes

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