Paper
18 March 2024 Flexible feedback intelligent routing algorithm based on DQN for large-scale LEO networks
Author Affiliations +
Proceedings Volume 13104, Advanced Fiber Laser Conference (AFL2023); 131043P (2024) https://doi.org/10.1117/12.3023513
Event: Advanced Fiber Laser Conference (AFL2023), 2023, Shenzhen, China
Abstract
The Low Earth Orbit (LEO) satellite constellation has the advantages of low-latency transmission and global coverage and has a wide range of applications in emergency rescue, aviation, and sea voyages. With the highly dynamic topologies, limited onboard computing resources, and large global routing computation overheads of the large-scale LEO constellation, centralized routing algorithms always encounter difficulties in such LEO satellite networks. Therefore, this paper proposes a flexible feedback intelligent routing algorithm based on deep Q-network (DQN) for large-scale LEO networks. By dynamically designing the reward function of DQN and adding a congestion alleviation scheme to the K-shortest path method in the training process, the delay and packet loss performances are improved. The delay performance is improved by 8%-12% over the Shortest Path First (SPF) algorithm, which is closer to the Shortest Delay First (SDF) algorithm with a minimum difference of only 6%. At the same time, the proposed algorithm has better packet loss performances than SPF and SDF algorithms to avoid congestion. When the congestion occurs, the algorithm can choose other paths.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Zongyi Luo, Shichao Jin, Tao Dong, and Jie Yin "Flexible feedback intelligent routing algorithm based on DQN for large-scale LEO networks", Proc. SPIE 13104, Advanced Fiber Laser Conference (AFL2023), 131043P (18 March 2024); https://doi.org/10.1117/12.3023513
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KEYWORDS
Satellites

Evolutionary algorithms

Data transmission

Deep learning

Mathematical optimization

Artificial intelligence

Satellite communications

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