Preventing instability in full echo Q-routing with adaptive learning rates

Kavalerov, Maxim V.; Shilova, Yuliya; Bezukladnikov, Igor I.

doi:10.1109/eiconrus.2017.7910517

Cited by 3 publications

(1 citation statement)

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“…Q-learning enabled the fuzzy system to conserve energy and ensured good communication performance. Being highly dynamical with a variable link quality, a couple of studies [ 36 , 37 ] proposed improved Q-learning-based routing protocols with adaptive learning rates. Meanwhile, others improved the exploration parameters of Q-learning to adapt to different mobile scenarios.…”

Section: Related Workmentioning

confidence: 99%

Delay-Aware and Link-Quality-Aware Geographical Routing Protocol for UANET via Dueling Deep Q-Network

Zhang

Qiu

2023

Sensors

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In an unmanned aerial vehicles ad hoc network (UANET), UAVs communicate with each other to accomplish intricate tasks collaboratively and cooperatively. However, the high mobility of UAVs, the variable link quality, and heavy traffic loads can lead to difficulties in finding an optimal communication path. We proposed a delay-aware and link-quality-aware geographical routing protocol for a UANET via the dueling deep Q-network (DLGR-2DQ) to address these problems. Firstly, the link quality was not only related to the physical layer metric, the signal-to-noise ratio, which was influenced by path loss and Doppler shifts, but also the expected transmission count of the data link layer. In addition, we also considered the total waiting time of packets in the candidate forwarding node in order to decrease the end-to-end delay. Then, we modeled the packet-forwarding process as a Markov decision process. We crafted an appropriate reward function that utilized the penalty value for each additional hop, total waiting time, and link quality to accelerate the learning of the dueling DQN algorithm. Finally, the simulation results illustrated that our proposed routing protocol outperformed others in terms of the packet delivery ratio and the average end-to-end delay.

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Section: Related Workmentioning

confidence: 99%