Sunday, 06 June
05:00 – 07:30
Johannes K. Fischer, Fraunhofer Heinrich-Hertz-Institut, Germany
Lida Galdino, Univ. College London, UK
Paolo Monti, Chalmers University of Technology, Sweden
Christine Tremblay, École de Technologie Supérieure, Montréal, Canada
5G and Beyond 5G services are expected to facilitate a transition towards smart communication infrastructures where network operations will account – in an automated fashion – for the specific end-user requirements and the network's status itself.
This workshop aims at stimulating a debate over which challenges should be overcome in the metro/core transport segment and what advantages can be foreseen when enabling this transition.
On the one hand, it is expected that network automation will help supporting dynamic and real-time provisioning of services (e.g., via cognitive, intent-based, zero-touch operations), optimizing the usage of infrastructure capacity (e.g., reactive/proactive re-routing, defragmentation, combining photonic layer programmable infrastructure with advanced software applications), and lowering CAPEX and OPEX costs. All these benefits will be achieved by a combination of intent-based operations, Artificial Intelligence (AI) mechanisms, and Machine Learning (ML) tools supported by a highly flexible and software-driven data plane providing detailed physical-layer information the data analytics framework.
On the other hand, it can be expected that the benefits brought by network automation will come at a cost in terms of an increased complexity to guarantee: (i) service quality, (ii) secure and reliable operations, and (iii) consistency of operations across the various technological and administrative domains.
Jesse Simsarian, Nokia, USA
Network Automation: Progress and Pitfalls
Harald Bock, Infinera, Germany
A Path Towards a Smart Zero-touch Transport Network
Stephan Neidlinger, ADVA, Germany
Real-life Achievements and Gaps in Autonomous Optical Networks
Yvan Pointurier, Huawei, France
Network Automation – an Equipment Maker's Perspective
Stefan Melin, Telia Company, Sweden
Key Areas for Improvements in Optical Networks –How Automation Can Help Us As an Operator
David Côté, Ciena, Canada
Action Recommendation Engine: Using AI to Automate Network Operations
Daniel Kilper, Trinity College Dublin, Ireland
Smarter Hardware vs Smarter Software: Where is the Sweet Spot?
Takeshi Hoshida, Fujitsu, Japan
Advanced Optical Monitoring in DSP-based Receiver
Cristina Rottondi, Politecnico di Torino, Italy
ML-based QoT Estimation with Small Training Datasets and Under Measurement Uncertainty