Reinforcement Learning-Based Routing Protocol in Underwater Sensor Networks 


Vol. 45,  No. 10, pp. 1716-1719, Oct.  2020
10.7840/kics.2020.45.10.1716


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  Abstract

This paper proposes a reinforcement learning based routing protocol to consider network topology in underwater sensor networks. Utilizing the reward value reflecting network topology, sensor node selects the next-forwarding node and thereby escaping the opposite direction routing to the sink and accordingly reducing the waste of resource. Computer simulation result shows that the propsed scheme outperforms QELAR in terms of latency and battery consumption.

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  Cite this article

[IEEE Style]

H. Kim and H. Cho, "Reinforcement Learning-Based Routing Protocol in Underwater Sensor Networks," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 10, pp. 1716-1719, 2020. DOI: 10.7840/kics.2020.45.10.1716.

[ACM Style]

Hee-won Kim and Ho-Shin Cho. 2020. Reinforcement Learning-Based Routing Protocol in Underwater Sensor Networks. The Journal of Korean Institute of Communications and Information Sciences, 45, 10, (2020), 1716-1719. DOI: 10.7840/kics.2020.45.10.1716.

[KICS Style]

Hee-won Kim and Ho-Shin Cho, "Reinforcement Learning-Based Routing Protocol in Underwater Sensor Networks," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 10, pp. 1716-1719, 10. 2020. (https://doi.org/10.7840/kics.2020.45.10.1716)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880