Machine Learning (ML) has already proven its benefits for network operation, being a sub-
domain of artificial intelligence, it is highly suitable for complex system representation. In this …

Failure detection is essential in optical networks as a result of the huge amount of traffic that
optical connections support. Additionally, the cause of failure needs to be identified so failed …

Machine Learning (ML) tools have recently been adopted for a wide range of automated
operations in optical networking, moving fundamental steps towards the paradigm of zero …

Fault Management Based on Machine Learning Page 1 W3G.3.pdf OFC 2019 © OSA 2019
Fault Management Based on Machine Learning [Invited] Luis Velasco and Danish Rafique …

The increase in computing capacity and the huge amount of available data have
significantly accelerated the use of artificial intelligence and machine learning algorithms to …

Innovations in optical networks created new technological challenges as routing and
spectrum allocation (RSA) problem, fragmented spectrum, the need for rapid and efficient …

In this paper, we explore the benefits of analysing the optical spectrum of lightpaths for soft-
failure detection and identification in Spectrum Switched Optical Network. We present a …

Increased levels of automation will be necessary in view of more stringent performance
requirements that next generation optical transport networks need to support in a near term …

Failures in the optical layer can affect the operation of the network as a whole, and the
services it supports. The current trend in optical networks is to reduce the operating margins …

Machine Learning Applications in Optical Networks | IEEE Conference Publication | IEEE
Xplore Machine Learning Applications in Optical Networks Abstract: After a generic introduction …