A fault-tolerant topology control algorithm for wireless ultraviolet light covert communication network in cluster UAV

Abstract

In the wireless ultraviolet sensor network, interference causes data retransmission, which is not conducive to communication between sensor nodes. Aiming at the serious communication interference problem of three-dimensional k-connected wireless ultraviolet light sensor network, this paper proposes a novel low-interference wireless ultraviolet network fault-tolerant topology control algorithm. The number of vertices disjoint paths between nodes and base stations is used as a fault-tolerance index to reduce network interference and ensure two-way fault tolerance between nodes and base stations. At the same time, genetic algorithm crossover and mutation operators are used to construct a particle swarm optimization algorithm, which is used to solve a reasonable power distribution scheme from the fault-tolerant network constructed by the 3D k-YG algorithm. The performance of the proposed algorithm is verified through simulation experiments. The experimental results show that the proposed algorithm can not only construct fault-tolerant topology, but also effectively reduce network interference.

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Acknowledgements

This paper is supported by Natural Science Foundation of National Natural Science Foundation of China (61971345), Scientific Research Program of Education Department of Shaanxi Province (17-JF024), Key Industrial Chain Innovation Program of Shaanxi Province (2017ZDCXL-GY-05-03), Science and Technology Program of Xi 'an Forest District (GX1921), Science and Technology Program of Yu Lin City (2019-145), Science and Technology Program of Xi 'an City (CXY1835(4)).

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Correspondence to Zhao Taifei.

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Taifei, Z., Shiyuan, S. A fault-tolerant topology control algorithm for wireless ultraviolet light covert communication network in cluster UAV. Photon Netw Commun (2021). https://doi.org/10.1007/s11107-021-00936-w

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Keywords

  • Wireless UV sensor network
  • Fault-tolerant topology control
  • Network interference
  • Particle swarm optimization