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A k-hop Constrained Reachability Based Proactive Connectivity Maintaining Mechanism of UAV Swarm Networks

Huibin Wang,
Ming Chen,
Xianglin Wei,

Abstract


Harsh or hostile environments may lead to node failure and connectivity degradation of a UAV swarm system. In order to maintain or restore the connectivity of a network in case of node failure, this paper proposes a mechanism to adjust the network topology to resist the impact caused by node failure. Firstly, a network model of a UAV swarm network based on k-hop constrained reachability is proposed. Secondly, a k-hop constrained reachability based proactive connectivity maintaining mechanism of UAV swarm network is presented. In this mechanism, each node identifies the network abnormality distributed according to k-hop reachability, and reports the observed abnormality to the master node; then, a virtual edge-based topology reconstruction algorithm is put forward for the master node to derive a topology reconstruction solution in a centralized way; afterwards, the solution is delivered to the slave nodes to reconfigure the network topology in parallel. Thirdly, a quantitative method is introduced to optimize the total travel distance of nodes, and a spanning tree-based method is designed to maintain the connectivity during the topology transformation process. Both theoretical analysis and simulation results have shown that: on the one hand, the proposed mechanism are effective in maintaining a UAV swarm’s connectivity in case of node failure; on the other hand, the proposed mechanism outperforms existing mechanisms in terms of fault tolerance, connectivity, and total travel distance, and it’s less affected by the failure rate.

Keywords


UAV swarm network, Network reconstruction, Connectivity maintaining, Algebraic connectivity

Citation Format:
Huibin Wang, Ming Chen, Xianglin Wei, "A k-hop Constrained Reachability Based Proactive Connectivity Maintaining Mechanism of UAV Swarm Networks," Journal of Internet Technology, vol. 24, no. 6 , pp. 1329-1341, Nov. 2023.

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