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An Abnormal Breakpoint Data Positioning Method of Wireless Sensor Network Based on Signal Reconstruction

  • Zhijie Liu (College of Mathematics and Computer, Xinyu University)
  • Received : 2022.07.22
  • Accepted : 2023.01.01
  • Published : 2023.06.30

Abstract

The existence of abnormal breakpoint data leads to poor channel balance in wireless sensor networks (WSN). To enhance the communication quality of WSNs, a method for positioning abnormal breakpoint data in WSNs on the basis of signal reconstruction is studied. The WSN signal is collected using compressed sensing theory; the common part of the associated data set is mined by exchanging common information among the cluster head nodes, and the independent parts are updated within each cluster head node. To solve the non-convergence problem in the distributed computing, the approximate term is introduced into the optimization objective function to make the sub-optimization problem strictly convex. And the decompressed sensing signal reconstruction problem is addressed by the alternating direction multiplier method to realize the distributed signal reconstruction of WSNs. Based on the reconstructed WSN signal, the abnormal breakpoint data is located according to the characteristic information of the cross-power spectrum. The proposed method can accurately acquire and reconstruct the signal, reduce the bit error rate during signal transmission, and enhance the communication quality of the experimental object.

Keywords

References

  1. Y. Liao, J. Ran, and X. Zhou, "Research on optimisation processing of spatiotemporal correlation temperature and humidity data based on wireless sensor networks in cigarette factory," The Journal of Engineering, vol. 2019, no. 23, pp. 9230-9235, https://doi.org/10.1049/joe.2018.9222
  2. N. Jan, A. H. Al-Bayatti, N. Alalwan, and A. I. Alzahrani, "An enhanced source location privacy based on data dissemination in wireless sensor networks (DeLP)," Sensors, vol. 19, no. 9, article no. 2050, 2019. https://doi.org/10.3390/s19092050
  3. R. Fotohi, S. Firoozi Bari, and M. Yusefi, "Securing wireless sensor networks against denial-of-sleep attacks using RSA cryptography algorithm and interlock protocol," International Journal of Communication Systems, vol. 33, no. 4, article no. e4234, 2020. https://doi.org/10.1002/dac.4234
  4. Y. Zhao, S. Xiao, H. Gan, L. Li, and L. Xiao, "Structural compressed network coding for data collection in cluster-based wireless sensor networks," IEICE Transactions on Communications, vol. 102, no. 11, pp. 2126-2138, 2019.
  5. J. Liu, P. Tong, X. Wang, B. Bai, and H. Dai, "UAV-aided data collection for information freshness in wireless sensor networks," IEEE Transactions on Wireless Communications, vol. 20, no. 4, pp. 2368-2382, 2021. https://doi.org/10.1109/TWC.2020.3041750
  6. L. Martinez-Villasenor and H. Ponce, "A concise review on sensor signal acquisition and transformation applied to human activity recognition and human-robot interaction," International Journal of Distributed Sensor Networks, vol. 15, no. 6, article no. 1550147719853987, 2019. https://doi.org/10.1177/1550147719853987
  7. Z. Z. Liu and S. N. Li, "WSNs compressed sensing signal reconstruction based on improved kernel fuzzy clustering and discrete differential evolution algorithm," Journal of Sensors, vol. 2019, article no. 7039510, 2019. https://doi.org/10.1155/2019/7039510
  8. H. Wang, W. Zhang, Y. Liang, and Y. Liu, "Efficient reconstruction architecture of compressed sensing and integrated source-channel decoder based on Reed Solomon code," IEEE Communications Letters, vol. 24, no. 2, pp. 239-243, 2020. https://doi.org/10.1109/LCOMM.2019.2954515
  9. S. Wang, H. Chen, Z. Pan, and J. Wang, "A reconstruction method for missing data in power system measurement using an improved generative adversarial network," Proceedings of the Chinese Society of Electrical Engineering, vol. 39, no. 1, pp. 56-64, 2019.
  10. A. Mehto, S. Tapaswi, and K. K. Pattanaik, "Virtual grid-based rendezvous point and sojourn location selection for energy and delay efficient data acquisition in wireless sensor networks with mobile sink," Wireless Networks, vol. 26, pp. 3763-3779, 2020. https://doi.org/10.1007/s11276-020-02293-4