An overview on application of machine learning techniques in optical networks

F Musumeci, C Rottondi, A Nag… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
Today's telecommunication networks have become sources of enormous amounts of widely
heterogeneous data. This information can be retrieved from network traffic traces, network …

Machine learning for network automation: overview, architecture, and applications [Invited Tutorial]

D Rafique, L Velasco - Journal of Optical Communications and …, 2018 - ieeexplore.ieee.org
Networks are complex interacting systems involving cloud operations, core and metro
transport, and mobile connectivity all the way to video streaming and similar user …

Machine learning models for estimating quality of transmission in DWDM networks

RM Morais, J Pedro - Journal of Optical Communications and …, 2018 - ieeexplore.ieee.org
It is estimated that 5G and the Internet of Things (IoT) will impact traffic, both in volume and
dynamicity, at unprecedented rates. Thus, to cost-efficiently accommodate these challenging …

A tutorial on machine learning for failure management in optical networks

F Musumeci, C Rottondi, G Corani… - Journal of Lightwave …, 2019 - opg.optica.org
Failure management plays a role of capital importance in optical networks to avoid service
disruptions and to satisfy customers' service level agreements. Machine learning (ML) …

Flexible technologies to increase optical network capacity

A Lord, SJ Savory, M Tornatore… - Proceedings of the …, 2022 - ieeexplore.ieee.org
Increased global traffic puts tough requirements not just on fiber communications links but
on the entire network. This manifests itself in multiple ways, including how to optimize …

Fiber-longitudinal anomaly position identification over multi-span transmission link out of receiver-end signals

T Tanimura, S Yoshida, K Tajima, S Oda… - Journal of Lightwave …, 2020 - opg.optica.org
We have developed a fiber-longitudinal monitor that visualizes distance-wise optical power
throughout the entire multi-span link by using the signal waveform obtained by a coherent …

Convolutional neural network-based optical performance monitoring for optical transport networks

T Tanimura, T Hoshida, T Kato, S Watanabe… - Journal of Optical …, 2019 - opg.optica.org
To address the open and diverse situation of future optical networks, it is necessary to find a
methodology to accurately estimate the value of a target quantity in an optical performance …

A survey on QoT prediction using machine learning in optical networks

L Zhang, X Li, Y Tang, J Xin, S Huang - Optical Fiber Technology, 2022 - Elsevier
In optical networks, a connection (eg, light-path and light-tree) is set up to carry data from its
source to destination (s). When the optical signal transmits through the fiber links and optical …

AI-based modeling and monitoring techniques for future intelligent elastic optical networks

X Liu, H Lun, M Fu, Y Fan, L Yi, W Hu, Q Zhuge - Applied Sciences, 2020 - mdpi.com
With the development of 5G technology, high definition video and internet of things, the
capacity demand for optical networks has been increasing dramatically. To fulfill the capacity …

Monitoring and diagnostic technologies using deep neural networks for predictive optical network maintenance

T Tanaka, T Inui, S Kawai, S Kuwabara… - Journal of Optical …, 2021 - opg.optica.org
In recent years, optical networks have become more complex due to traffic increase and
service diversification, and it has become increasingly difficult for network operators to …