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An overview of ML-based applications for next generation optical networks

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Abstract

Over the past few decades, the demand for the capacity and reliability of optical networks has continued to grow. In the meantime, optical networks with larger knowledge scales have become sources of numerous heterogeneous data. In order to handle these new challenges, many issues need to be resolved, among which the low-margin optical networks design, power optimization, routing and wavelength assignment (RWA), failure management are quite important. However, the use of traditional algorithms in the above four applications shows some shortcomings. Fortunately, artificial intelligence (AI), especially machine learning (ML), is regarded as one of the most promising methods to overcome these shortcomings. In this study, we review the applications of ML methods in solving these four issues. Although many ML-based researches have emerged, the applications of ML techniques in optical networks still face challenges. Therefore, we also discuss some possible future directions of investigating ML-based approaches in optical networks.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant No. 61801291), Shanghai Rising-Star Program (Grant No. 19QA1404600), and National Key R&D Program of China (Grant No. 2018YFB-1801200).

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  1. Ruoxuan GAO and Lei LIU have the same contribution to this work.

Authors and Affiliations

  1. Shanghai Institute for Advanced Communication and Data Science, State Key Laboratory of Advanced Optical Communication Systems and Networks, Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Ruoxuan Gao, Lei Liu, Xiaomin Liu, Huazhi Lun, Lilin Yi, Weisheng Hu & Qunbi Zhuge

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  1. Ruoxuan Gao
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  2. Lei Liu
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  3. Xiaomin Liu
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Correspondence to Qunbi Zhuge.

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Gao, R., Liu, L., Liu, X. et al. An overview of ML-based applications for next generation optical networks. Sci. China Inf. Sci. 63, 160302 (2020). https://doi.org/10.1007/s11432-020-2874-y

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