Article
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Influence of Removing Leaf Node Neighbors on Network Controllability
Version 1
: Received: 9 May 2023 / Approved: 10 May 2023 / Online: 10 May 2023 (05:21:06 CEST)
A peer-reviewed article of this Preprint also exists.
Wu, C.; Xu, S.; Yu, Z.; Li, J. Influence of Removing Leaf Node Neighbors on Network Controllability. Entropy 2023, 25, 945. Wu, C.; Xu, S.; Yu, Z.; Li, J. Influence of Removing Leaf Node Neighbors on Network Controllability. Entropy 2023, 25, 945.
Abstract
From the perspective of network attackers, finding attack sequences that can make significant damage on network controllability is an important task, which also helps defenders improve the robustness during network constructions. Therefore, developing effective attack strategies is a key aspect of research on network controllability and its robustness. In this paper, we propose a Leaf Node Neighbor-based Attack (LNNA) strategy that can effectively disrupt the controllability of undirected networks. The LNNA strategy targets the neighbors of leaf nodes, and when there are no leaf nodes in the network, the strategy attacks the neighbors of nodes with a higher degree to produce the leaf nodes. Results from simulations on synthetic and real-world networks demonstrate the effectiveness of the proposed method. In particular, our findings suggest that removing neighbors of low-degree nodes (i.e., nodes with degree 1 or 2) can significantly reduce the controllability robustness of networks. Thus, protecting such low-degree nodes and their neighbors during network construction can lead to networks with improved controllability robustness.
Keywords
controllability; controllability robustness; undirected networks; attack strategy
Subject
Engineering, Control and Systems Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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