TY - GEN
T1 - A Distributed Critical Node Detection Algorithm for UAV Swarm Networks
AU - He, Zihang
AU - Gou, Haosong
AU - Wu, Xiong
AU - Zhang, Gaoyi
AU - Du, Pengfei
AU - Zhai, Daosen
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Unmanned aerial vehicle (UAV) swarm can be widely used in cooperative detection and strike across wide geographic areas. To support the collaboration of multiple UAVs, a connected network topology is essential. Thus, critical nodes, whose removal will disconnect the network into two or more separate components, will play an important role in UAV swarm networks. This paper investigate the distributed critical node detection algorithm for UAV swarm networks. Firstly, we analyze the logical relationship between critical node, robustness, and k-hop subgraph. Guided by the analysis, we propose a distributed critical node detection algorithm by using the geometrical relationship of neighbors and the k-hop local topology. Abundant simulation results indicate that the proposed algorithms can strike a good balance between accuracy and overhead and greatly outperform the global detection algorithms especially in large-scale networks. Besides, the simulation study provides some useful design guidance for robust topology control of UAV swarm networks.
AB - Unmanned aerial vehicle (UAV) swarm can be widely used in cooperative detection and strike across wide geographic areas. To support the collaboration of multiple UAVs, a connected network topology is essential. Thus, critical nodes, whose removal will disconnect the network into two or more separate components, will play an important role in UAV swarm networks. This paper investigate the distributed critical node detection algorithm for UAV swarm networks. Firstly, we analyze the logical relationship between critical node, robustness, and k-hop subgraph. Guided by the analysis, we propose a distributed critical node detection algorithm by using the geometrical relationship of neighbors and the k-hop local topology. Abundant simulation results indicate that the proposed algorithms can strike a good balance between accuracy and overhead and greatly outperform the global detection algorithms especially in large-scale networks. Besides, the simulation study provides some useful design guidance for robust topology control of UAV swarm networks.
KW - Unmanned aerial vehicle swarm
KW - graph theory
KW - network connectivity
KW - topology control
UR - http://www.scopus.com/inward/record.url?scp=105000653356&partnerID=8YFLogxK
U2 - 10.1109/CCPQT64497.2024.00045
DO - 10.1109/CCPQT64497.2024.00045
M3 - 会议稿件
AN - SCOPUS:105000653356
T3 - Proceedings - 2024 3rd International Conference on Computing, Communication, Perception and Quantum Technology, CCPQT 2024
SP - 200
EP - 204
BT - Proceedings - 2024 3rd International Conference on Computing, Communication, Perception and Quantum Technology, CCPQT 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Computing, Communication, Perception and Quantum Technology, CCPQT 2024
Y2 - 25 October 2024 through 27 October 2024
ER -