Abstract
In Underwater Sensor Networks (UWSNs), the location information of sensor nodes is essential for making the measured data meaningful. However, UWSNs have a complex node deployment environment. Node mobility caused by ocean currents and other factors would lead to a bigger ranging error and make some nodes cannot receive enough data packets. In this paper, a Localization algorithm based on a Single Mobile Beacon (LSMB) is proposed. LSMB makes use of the attenuation law of signal strength and the geometric relationship between a sensor node and the path of the mobile beacon, reducing the impact of random error on distance measurement. On this basis, by analyzing the overall movement trends of sensor nodes, this paper analyzes and studies the counter-current movement and downstream movement of the mobile beacon respectively, so as to make LSMB suitable for dynamic marine environment. The simulation shows that the algorithm reduces the impact of node mobility on localization and has small average localization error.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Su, Y., Guo, L., Jin, Z., Fu, X.: A mobile-beacon-based iterative localization mechanism in large-scale underwater acoustic sensor networks. IEEE Internet Things J. 8(5), 3653–3664 (2021). https://doi.org/10.1109/JIOT.2020.3023556
Ullah, I.: A review of underwater localization techniques, algorithms, and challenges. J. Sens. 2020 (2020). https://doi.org/10.1155/2020/6403161
Yan, J., Meng, Y., Yang, X., Luo, X., Guan, X.: Privacy-preserving localization for underwater sensor networks via deep reinforcement learning. IEEE Trans. Inf. Forensics Secur. 16, 1880–1895 (2021). https://doi.org/10.1109/TIFS.2020.3045320
Mridula, K., Ameer, P.: Localization under anchor node uncertainty for underwater acoustic sensor networks. Int. J. Commun. Syst. 31, e3445 (2017). https://doi.org/10.1002/dac.3445
Karagol, S., Yildiz, D.: A path planning model based on nested regular hexagons using weighted centroid localization. Int. J. Commun. Syst. 35(1), e5015 (2022). https://doi.org/10.1002/dac.5015
Huang, H., Zheng, Y.R.: Node localization with AOA assistance in multi-hop underwater sensor networks. Ad Hoc Netw. 78, 32–41 (2018). https://doi.org/10.1016/j.adhoc.2018.05.005
Luo, J., Yang, Y., Wang, Z., Chen, Y.: Localization algorithm for underwater sensor network: a review. IEEE Internet Things J. 8(17), 13126–13144 (2021). https://doi.org/10.1109/JIOT.2021.3081918
Osborn, J., Qualls, S., Canning, J., Anderson, M., Edwards, D., Wolbrecht, E.: AUV state estimation and navigation to compensate for ocean currents. In: OCEANS 2015 - MTS/IEEE Washington, pp. 1–5 (2015). https://doi.org/10.23919/OCEANS.2015.7401906
Bhairavi, R., Sudha, G.F.: Modified dive and rise technique incorporating enhanced weighted centroid localization algorithm with ocean current mobility model in underwater acoustic sensor networks. In: Ranganathan, G., Chen, J., Rocha, Á. (eds.) Inventive Communication and Computational Technologies. LNNS, vol. 89, pp. 569–582. Springer, Singapore (2020). https://doi.org/10.1007/978-981-15-0146-3_54
Koutsonikolas, D., Das, S.M., Hu, Y.C.: Path planning of mobile landmarks for localization in wireless sensor networks. Comput. Commun. 30(13), 2577–2592 (2007). https://doi.org/10.1016/j.comcom.2007.05.048
Beerens, S., Ridderinkhof, H., Zimmerman, J.: An analytical study of chaotic stirring in tidal areas. Chaos Solitons Fractals 4(6), 1011–1029 (1994). https://doi.org/10.1016/0960-0779(94)90136-8
Caruso, A., Paparella, F., Vieira, L.F.M., Erol, M., Gerla, M.: The meandering current mobility model and its impact on underwater mobile sensor networks. In: IEEE INFOCOM 2008 - The 27th Conference on Computer Communications, pp. 221–225 (2008). https://doi.org/10.1109/INFOCOM.2008.53
Sun, Y., Yuan, Y., Xu, Q., Hua, C.: A mobile anchor node assisted RSSI localization scheme in underwater wireless sensor networks. Sensors 19, 4369 (2019). https://doi.org/10.3390/s19204369
Acknowledgement
This work was supported by Natural Science Foundation of Shandong Province (No. ZR2020MF061).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Guo, Y., Niu, L., Zhang, R., Cao, H., Xu, J. (2022). Localization for Underwater Sensor Networks Based on a Mobile Beacon. In: Wang, L., Segal, M., Chen, J., Qiu, T. (eds) Wireless Algorithms, Systems, and Applications. WASA 2022. Lecture Notes in Computer Science, vol 13473. Springer, Cham. https://doi.org/10.1007/978-3-031-19211-1_20
Download citation
DOI: https://doi.org/10.1007/978-3-031-19211-1_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-19210-4
Online ISBN: 978-3-031-19211-1
eBook Packages: Computer ScienceComputer Science (R0)