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LEER: Layer-Based Energy-Efficient Routing Protocol for Underwater Sensor Networks

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Abstract

Acoustic signals are used for communication in underwater sensor networks (UWSNs) because radio signals attenuate heavily when propagating in water, while optical signals have large scattering in water. Data transmission in UWSNs faces great challenges due to the characteristics of underwater acoustic channels. Moreover, high energy consumption and long latency bring about increased challenges for the designs of routing protocols in UWSNs. In this paper, we propose a routing protocol called Layer-based Energy-Efficient Routing (LEER) protocol to address the route failure problem with greedy routing, as well as the long end-to-end delay and high energy consumption problems. In LEER, each node extracts the layer field information from hello packets received and updates its own layer to avoid the problem of routing a packet to a void area. All nodes with the LEER protocol forward packets to a sink node without the need for any location information. Simulation results show that the LEER protocol outperforms the depth-based routing (DBR) protocol in terms of the delivery rate and end-to-end delay.

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  1. Extended author information available on the last page of the article.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China under grant No. 61962052 and 61902273, the Innovation Team Foundation of Qinghai Office of Science and Technology under grant No. 2020-ZJ-903, the Hebei IoT Monitoring Center under grant No.3142016020, and the Chunhui Program of Ministry of Education of China.

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Authors and Affiliations

  1. School of Computer Science, Qinghai Normal University, Xining, China

    Jianlian Zhu, Xiujuan Du, Duoliang Han, Lijuan Wang & Meiju Li

  2. Academy of Plateau Science and Sustainability, Xining, China

    Xiujuan Du

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  1. Jianlian Zhu
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  2. Xiujuan Du
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Correspondence to Xiujuan Du.

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Zhu, J., Du, X., Han, D. et al. LEER: Layer-Based Energy-Efficient Routing Protocol for Underwater Sensor Networks. Mobile Netw Appl 27, 502–509 (2022). https://doi.org/10.1007/s11036-020-01693-2

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  • DOI: https://doi.org/10.1007/s11036-020-01693-2

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