Autonomous operations in optical networks

Cita com:
hdl:2117/330309
Document typeConference report
Defense date2019
Rights accessOpen Access
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ProjectMETRO-HAUL - METRO High bandwidth, 5G Application-aware optical network, with edge storage, compUte and low Latency (EC-H2020-761727)
COGNITIVE 5G APPLICATION-AWARE OPTICAL METRO NETWORKS INTEGRATING MONITORING, DATA ANALYTICS AND OPTIMIZATION (AEI-TEC2017-90097-R)
COGNITIVE 5G APPLICATION-AWARE OPTICAL METRO NETWORKS INTEGRATING MONITORING, DATA ANALYTICS AND OPTIMIZATION (AEI-TEC2017-90097-R)
Abstract
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 paper, basic ML concepts are reviewed, as well as its integration into existing network control and management planes. Then, a use case focused on soft-failure detection is presented in detail covering optical spectrum analysis and ML algorithms; the technique relies on the widespread deployment of cost-effective optical spectrum analyzer (OSA). Finally, the retrieved optical parameters are analyzed using ML algorithms giving rise to illustrative results.
Description
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CitationPérez-Vela, A.; Ruiz, M.; Velasco, L. Autonomous operations in optical networks. A: International Conference on Transparent Optical Networks. "ICTON 2019, 21st International Conference on Transparent Optical Networks: 9-13 July 2019, Angers France". 2019, p. 1-4. ISBN 978-1-7281-2779-8. DOI 10.1109/ICTON.2019.8840177.
ISBN978-1-7281-2779-8
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