Forum Numerica - Optical Network Automation

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Operators’ network management continuously measure network health by collecting data from the deployed network devices; data is used mainly for performance reporting and diagnosing network problems after failures, as well as by human capacity planners to predict future traffic growth. Typically, these network management tools are generally reactive and require significant human effort and skills to operate effectively. As optical networks evolve to fulfil highly flexible connectivity and dynamicity requirements, and supporting ultra-low latency services, they must also provide reliable connectivity and increased network resource efficiency. Therefore, reactive human-based network measurement and management will be a limiting factor in the size and scale of these new networks. Future optical networks must support fully automated management, providing: i) dynamic resource re-optimization to rapidly adapt network resources based on predicted conditions and events; ii) identify service degradation conditions that will eventually impact connectivity and highlight critical devices and links for further inspection; and iii) augment rapid protection schemes if a failure is predicted or detected, and facilitate resource optimization after restoration events. Applying automation techniques to network management requires both the collection of data from a variety of sources at various time frequencies, but it must also support the capability to extract knowledge and derive insight for performance monitoring, troubleshooting, and maintain network service continuity. Innovative analytics algorithms must be developed to derive meaningful input to the entities that orchestrate and control network resources; these control elements must also be capable of proactively programming the underlying optical infrastructure. In this talk, I review the emerging requirements for optical network management automation, the capabilities of current optical systems, and the development and standardization status of data  models and protocols to facilitate automated network monitoring. Finally, I propose an architecture to provide Monitoring and Data Analytics (MDA) capabilities. I present illustrative control loops for advanced network monitoring use cases, and the findings that validate the usefulness of MDA to provide automated optical network management.

Prof. Luis Velasco
http://people.ac.upc.edu/lvelasco/
Universitat Politecnica de Catalunya (UPC), Optical Communications Group

He received the B.Sc. degree in Telecommunications Engineering from Universidad Politecnica de Madrid (UPM) in 1989, the M.Sc. degree in Physics from Universidad Complutense de Madrid (UCM) in 1993, the Master degree in Business Administration (MBA) from UPM in 2001, and the PhD degree from Universitat Politecnica de Catalunya (UPC) in 2009.
In 1989 he joined Telefonica of Spain and was involved on the specifications and first office application of Telefonica's SDH transport network. In 2004 he joined UPC, where currently he is a full professor at the Department of Computers Architecture (DAC) and senior researcher at the Advanced Broadband Communications Center (CCABA).
He has co-authored more than 200 papers in peer-reviewed International Journals and Conferences, as well as two books related to Elastic Optical Networks.
He is serving as an Associate Editor of the IEEE/OSA Journal of Optical Communications and Networking (JOCN) and in the TPC of several international conferences as well as reviewer of international journals.
He has participated in various IST FP-6, FP-7, and H2020 European research projects such as NOBEL 2, e-Photon/ONe+, DICONET, BONE, STRONGEST, IDEALIST, GÉANT, and METRO-HAUL.
He received the ICREA Academia award in engineering sciences in 2015.
His interests include monitoring and data analytics aspects for the service and network layers.