Real-time traffic prediction for PON based on adaptive online learning

Lei Wang; Haoyu Wang; Jing Qi; Xianglong Liu; Haoran Wang

doi:10.1117/12.3023572

18 March 2024 Real-time traffic prediction for PON based on adaptive online learning

Lei Wang, Haoyu Wang, Jing Qi, Xianglong Liu, Haoran Wang

Proceedings Volume 13104, Advanced Fiber Laser Conference (AFL2023); 131044A (2024) https://doi.org/10.1117/12.3023572
Event: Advanced Fiber Laser Conference (AFL2023), 2023, Shenzhen, China

Abstract

In this paper, we proposes an online learning-based Long Short-Term Memory (LSTM) model which dynamically updates model parameters in real-time at a lower computational cost. This makes it possible to quickly adjust to the data's dynamic changes. The usefulness and potential of the model in real-time prediction scenarios are demonstrated by the experimental findings, which show that it performs better in real-time training situations than typical offline training models.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Lei Wang, Haoyu Wang, Jing Qi, Xianglong Liu, and Haoran Wang "Real-time traffic prediction for PON based on adaptive online learning", Proc. SPIE 13104, Advanced Fiber Laser Conference (AFL2023), 131044A (18 March 2024); https://doi.org/10.1117/12.3023572

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