Optical path management based on machine learning for optical networks

R. Shiraki; Y. Mori; H. Hasegawa

doi:10.1117/12.2649581

15 March 2023 Optical path management based on machine learning for optical networks

R. Shiraki, Y. Mori, H. Hasegawa

Author Affiliations +

Proceedings Volume 12429, Next-Generation Optical Communication: Components, Sub-Systems, and Systems XII; 124290M (2023) https://doi.org/10.1117/12.2649581
Event: SPIE OPTO, 2023, San Francisco, California, United States

Abstract

The popularity of high-capacity communication services such as video streaming and cloud computing has accelerated the growth in IP traffic. In order to effectively manage and maintain networking systems, various intelligent technologies based on software-defined networking (SDN) have been widely studied. An SDN system that offers flexible optical path management exploiting optical performance monitoring, digital signal processing, and resource allocation is expected to realize higher capacity networks by lowering margins needed to offset system uncertainty. In this paper, we provide a comprehensive survey of optical path management schemes based on machine learning.

Conference Presentation

Citation Download Citation

R. Shiraki, Y. Mori, and H. Hasegawa "Optical path management based on machine learning for optical networks", Proc. SPIE 12429, Next-Generation Optical Communication: Components, Sub-Systems, and Systems XII, 124290M (15 March 2023); https://doi.org/10.1117/12.2649581

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