Wireless Routing Protocol with Periodic Q-Table Update 


Vol. 45,  No. 12, pp. 2099-2105, Dec.  2020
10.7840/kics.2020.45.12.2099


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  Abstract

Researches to enhance network stability and reduce latency by applying reinforcement learning in the wireless routing are being carried on. Existing wireless routing algorithms rely on neighbor information, such as the distance to the parent node or the average time taken to deliver the packet to the parent node when the node selects the parent node. In this paper, we propose to utilize the Q-learning, a kind of reinforcement learning, with periodically updating the whole network information and suggest to apply to RPL(Routing protocol for low power and lossy network), the standard routing protocol for low-power low-loss networks. The proposed algorithm can achieve the network load balancing, compared to the existing routing algorithm where the traffic load is high. Through simulation, we compared the performance with the existing Full echo Q-routing and verified that the proposed algorithm shows better performance in terms of PDR (Packet delivery rate) and latency.

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  Cite this article

[IEEE Style]

T. Kim and J. Joung, "Wireless Routing Protocol with Periodic Q-Table Update," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 12, pp. 2099-2105, 2020. DOI: 10.7840/kics.2020.45.12.2099.

[ACM Style]

Taejung Kim and Jinoo Joung. 2020. Wireless Routing Protocol with Periodic Q-Table Update. The Journal of Korean Institute of Communications and Information Sciences, 45, 12, (2020), 2099-2105. DOI: 10.7840/kics.2020.45.12.2099.

[KICS Style]

Taejung Kim and Jinoo Joung, "Wireless Routing Protocol with Periodic Q-Table Update," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 12, pp. 2099-2105, 12. 2020. (https://doi.org/10.7840/kics.2020.45.12.2099)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880