A Node Location Algorithm Based on Node Movement Prediction in Underwater Acoustic Sensor Networks
المؤلف | Zhang, Wenbo |
المؤلف | Han, Guangjie |
المؤلف | Wang, Xin |
المؤلف | Guizani, Mohsen |
المؤلف | Fan, Kaiguo |
المؤلف | Shu, Lei |
تاريخ الإتاحة | 2022-12-14T14:26:52Z |
تاريخ النشر | 2020-03-01 |
اسم المنشور | IEEE Transactions on Vehicular Technology |
المعرّف | http://dx.doi.org/10.1109/TVT.2019.2963406 |
الاقتباس | Zhang, W., Han, G., Wang, X., Guizani, M., Fan, K., & Shu, L. (2020). A node location algorithm based on node movement prediction in underwater acoustic sensor networks. IEEE Transactions on Vehicular Technology, 69(3), 3166-3178. |
الرقم المعياري الدولي للكتاب | 00189545 |
الملخص | Aiming at the problems of the low mobility, low location accuracy, high communication overhead, and high energy consumption of sensor nodes in underwater acoustic sensor networks, the MPL (movement prediction location) algorithm is proposed in this article. The algorithm is divided into two stages: mobile prediction and node location. In the node location phase, a TOA (time of arrival)-based ranging strategy is first proposed to reduce communication overhead and energy consumption. Then, after dimension reduction processing, the grey wolf optimizer (GWO) is used to find the optimal location of the secondary nodes with low location accuracy. Finally, the node location is obtained and the node movement prediction stage is entered. In coastal areas, the tidal phenomenon is the main factor leading to node movement; thus, a more practical node movement model is constructed by combining the tidal model with node stress. Therefore, in the movement prediction stage, the velocity and position of each time point in the prediction window are predicted according to the node movement model, and underwater location is then completed. Finally, the proposed MPL algorithm is simulated and analyzed; the simulation results show that the proposed MPL algorithm has higher localization performance compared with the LSLS, SLMP, and GA-SLMP algorithms. Additionally, the proposed MPL algorithm not only effectively reduces the network communication overhead and energy consumption, but also improves the network location coverage and node location accuracy. |
راعي المشروع | The work was supported in part by the National Key Research and Development Program under Grant 2018YFC0407900, in part by the National Natural Science Foundation of China under Grant 61971206, in part by the Open Fund of State Key Laboratory of Acoustics under Grant SKLA201901, in part by the China Academy of Military Sciences Fund (2019), in part by the Liaoning BaiQianWan Talents Program (2016), and in part by the Natural Science Foundation of Liaoning Province Project under Grant 20170540793. |
اللغة | en |
الناشر | Institute of Electrical and Electronics Engineers Inc. |
الموضوع | motion model movement prediction location ranging strategy Underwater acoustic sensor networks Wolf algorithm optimizer |
النوع | Article |
الصفحات | 3166-3178 |
رقم العدد | 3 |
رقم المجلد | 69 |
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