Learning quantile QoT models to address uncertainty over unseen lightpaths
Uncertainty in quality-of-transmission (QoT) estimation is traditionally addressed through
empirical, myopic margins, ignoring the fact that each unseen lightpath is subject to different …
empirical, myopic margins, ignoring the fact that each unseen lightpath is subject to different …
Machine-learning-based impairment-aware dynamic RMSCA in multi-core elastic optical networks
JL Ravipudi, M Brandt-Pearce - Journal of Optical …, 2024 - ieeexplore.ieee.org
This paper presents a routing, modulation, spectrum, and core assignment (RMSCA)
algorithm for space-division-multiplexing-based elastic optical networks (SDM-EONs) …
algorithm for space-division-multiplexing-based elastic optical networks (SDM-EONs) …
Representing uncertainty in deep QoT models
H Maryam, T Panayiotou… - 2022 20th Mediterranean …, 2022 - ieeexplore.ieee.org
Quality-of-transmission (QoT) estimation of unestablished lightpaths has been extensively
studied in the literature through the development of linear physical layer models (PLMs) and …
studied in the literature through the development of linear physical layer models (PLMs) and …
Machine-learning-assisted failure prediction in microwave networks based on equipment alarms
Modern microwave networks must cope with strict Quality of Services (QoS) requirements,
such as low latency, high bandwidth and high availability. As network failures can affect …
such as low latency, high bandwidth and high availability. As network failures can affect …
Lifelong QoT prediction: an adaptation to real-world optical networks
Q Wang, Z Cai, FN Khan - Journal of Optical Communications and …, 2024 - opg.optica.org
Predicting the quality of transmission (QoT) is a critical task in the management and
optimization of modern fiber-optic networks. Traditional machine learning (ML) QoT …
optimization of modern fiber-optic networks. Traditional machine learning (ML) QoT …
Modeling soft-failure evolution for triggering timely repair with low QoT margins
In this work, the capabilities of an encoder-decoder learning framework are leveraged to
predict soft-failure evolution over a long future horizon. This enables the triggering of timely …
predict soft-failure evolution over a long future horizon. This enables the triggering of timely …
[PDF][PDF] Overview of ML-aided QoT Estimation in Optical Networks: A Perspective of Model Generalization
The past decade has witnessed a tremendous stride toward automated and intelligent
optical networking thanks to the revolutionary development in machine learning (ML) …
optical networking thanks to the revolutionary development in machine learning (ML) …
Optical path management based on machine learning for optical networks
R Shiraki, Y Mori, H Hasegawa - Next-Generation Optical …, 2023 - spiedigitallibrary.org
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 …
computing has accelerated the growth in IP traffic. In order to effectively manage and …