The Optical Networking and Communication
Conference & Exhibition

Los Angeles Convention Center,
Los Angeles, California, USA

Will Machine Learning and Big-data Analytics Relieve us From the Complexity of System and Network Engineering?

Event type: Workshop


Sethumadhavan Chandrasekhar, Nokia Bell Labs, USA; Neil Guerrero Gonzales, Universidad Nacional de Colombia, Colombia; Massimo Tornatore, Politecnico di Milano, Itlay


Complexity of optical networks is growing rapidly. On a system side, coherent technologies introduced a plethora of adjustable design parameters (modulation formats, symbol rates, among others) to optimize transport systems. On a networking side, dynamic control, as in SDN, promises to enable long-awaited on-demand reconfiguration and virtualization. This variety of “degrees of freedom” does pose challenges when deciding the best system configuration. This workshop examines the application of machine learning and big-data analytics as disruptive solutions to relieve design of future networks/systems from such complexity. These techniques allow to infer, from monitored data (signal quality, traffic samples, etc.), useful characteristics that cannot be easily measured. Speakers from academia, vendors, and operators will debate how beneficial these techniques could be and which are their killer applications.

Peter Winzer, Nokia Bell Labs, USA
Jose Manuel, Estaran Tolosa  Nokia Bell Labs, France
Darko Zibar, Technical University of Denmark, Denmark
Maurice O'Sullivan, Ciena, Canada
Moises Ribeiro, Universidade Federal do Espírito Santo, Brazil
Dimitra Simeonidou, University of Bristol, UK
Vishnu Shukla, Verizon & OIF, USA
Shoukei Kobayashi, NTT, Japan
Luis Velasco, UPC, Spain
Satyajeet Ahuja, Facebook, USA
Huiying Xu, Huawei, China

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