Machine learning for intelligent optical networks: A comprehensive survey
With the rapid development of Internet and communication systems, both in the aspect of
services and technologies, communication networks have been suffering increasing …
services and technologies, communication networks have been suffering increasing …
A review of machine learning-based failure management in optical networks
Failure management plays a significant role in optical networks. It ensures secure operation,
mitigates potential risks, and executes proactive protection. Machine learning (ML) is …
mitigates potential risks, and executes proactive protection. Machine learning (ML) is …
Building a digital twin for intelligent optical networks [Invited Tutorial]
To support the development of intelligent optical networks, accurate modeling of the physical
layer is crucial. Digital twin (DT) modeling, which relies on continuous learning with real-time …
layer is crucial. Digital twin (DT) modeling, which relies on continuous learning with real-time …
Deep learning-based real-time analysis of lightpath optical constellations
M Ruiz, D Sequeira, L Velasco - Journal of Optical Communications …, 2022 - opg.optica.org
Optical network automation requires accurate physical layer models, not only for
provisioning but also for real-time analysis. In particular, in-phase (I) and quadrature (Q) …
provisioning but also for real-time analysis. In particular, in-phase (I) and quadrature (Q) …
OCATA: a deep-learning-based digital twin for the optical time domain
The development of digital twins to represent the optical transport network might enable
multiple applications for network operation, including automation and fault management. In …
multiple applications for network operation, including automation and fault management. In …
Optical network security management: requirements, architecture, and efficient machine learning models for detection of evolving threats
As the communication infrastructure that sustains critical societal services, optical networks
need to function in a secure and agile way. Thus, cognitive and automated security …
need to function in a secure and agile way. Thus, cognitive and automated security …
Soft-failure detection, localization, identification, and severity prediction by estimating QoT model input parameters
The performance of optical devices can degrade because of aging and external causes like,
for example, temperature variations. Such degradation might start with a low impact on the …
for example, temperature variations. Such degradation might start with a low impact on the …
[HTML][HTML] AI-based modeling and monitoring techniques for future intelligent elastic optical networks
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 …
capacity demand for optical networks has been increasing dramatically. To fulfill the capacity …
Machine learning for optical network security monitoring: A practical perspective
In order to accomplish cost-efficient management of complex optical communication
networks, operators are seeking automation of network diagnosis and management by …
networks, operators are seeking automation of network diagnosis and management by …
Data augmentation to improve performance of neural networks for failure management in optical networks
Despite the increased exploration of machine learning (ML) techniques for the realization of
autonomous optical networks, less attention has been paid to data quality, which is critical …
autonomous optical networks, less attention has been paid to data quality, which is critical …