Toward robust network controllability: Insights and future directions

Yang Lou*, Lin Wang, Guanrong Chen

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Network controllability refers to the ability of a networked system to drive its state to any desired configuration through control inputs. Controllability robustness ensures that this capability is maintained or retained under structural variations, such as node or edge failures caused by malicious attacks or random perturbations, which is critically important for real-world networks. This paper reviews existing metrics, evaluation methods and optimization strategies for controllability robustness, introducing also modeling techniques for attack processes. Analytical techniques, empirical simulations and machine learning-based approaches are presented, highlighting their respective advantages and limitations. Finally, some future directions are briefly discussed in four key areas: metrics design, evaluation refinement, optimization algorithms, and attack process modeling. By addressing these challenges, it is expected to develop more robust and stronger resilient networked systems.

Copyright © 2025 The author(s)
Original languageEnglish
Article number41003
Number of pages7
JournalEurophysics Letters
Volume149
Issue number4
Online published17 Feb 2025
DOIs
Publication statusPublished - Feb 2025

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