Towards Self Driven Networks
10/12 April 2018 / Marriott Paris

AI Net Conference 2018: Towards Self Driven Networks

AI and Machine Learning are being hyped in almost every imaginable field. However, networking is lagging far behind in the development and deployment of these new techniques.

And yet AI can be effectively used in many networking areas, such as fault isolation, intrusion detection, event correlation, log analysis, capacity planning, and design optimization, just to name a few.

New paradigms: SDN, 5G & IoT, Network Analytics

The AI Net conference will demonstrate that the rise of two recent paradigms: Software-Defined Networking (SDN) and Network Analytics (NA), will facilitate the adoption of these techniques in the context of network operation and control.

Moreover, cognitive network management has been widely accepted as the current orientation for an efficient, agile and automated management operations for 5G & IoT networks.

The agenda: AI for service automation and network management, Internet security monitoring, machine learning vs rule based systems, Analytics and Telemetry

The conference will gather a set of renowned experts coming from the research side (Inria, Tokyo City University, Cataluna University), from operators (BT, Orange, Expedia) industrials (Juniper Networks, Nokia, Huawei, Cisco, Aria Networks) and software companies (HPe, Brocade, CA).

The agenda will address the following sessions:
  • Requirements and Expectations for Network AI
  • Telemetry, Data streaming, and Data Warehouse
  • Machine Learning and AI for Network Analytics 
  • AI for network automation and service design
  • Machine Learning techniques
  • Security applications and Prediction
  • Field trial, Production Network Experience
  • AI and IoT, 5G
A tutorial session has been designed for professionals who haven’t yet learned about AI and have a strong network background. The tutorial also presents results from surveys realised by Ovum and Rethink Research. 

Finally, the agenda will include a constructive and informational debate on « Machine learning versus rule-based systems ».

The Speakers

Sam Aldrin

Michael Azoff

Dean Bubley
Disruptive Analysis

Albert Cabelos
Catalunya Univ.

Laurent Ciavaglia

Robert Curran
Aria networks

John Evans

Luyuan Fang

Jérôme François

Caroline Gabriel
Rethink Research

Imen Grida Ben Yahia
Orange Labs

Nir Halachmi

Shen Jiang
IETF, Huawei

Steve Kohalmi
juniper Networks

Ulrich Kohn
Adva Optical

Kireeti Kompella
juniper Networks

Dr. Kim Larsen
Magyar Telekom

David Meyer

Victor Muntés Mulero
CA Technologies

Detlef Nauck

Kumar Reddy

Kohei Shiomoto
Tokyo University

Niloufar Tayebi

Roland Thienpont

Jean-Marc Uzé