5
Experiences in operational networks.
THIRD EDITION ★ 30 JUNE/02 JULY 2020 ★ MARRIOTT HOTEL & CONFERENCE CENTER ★ PARIS
Coronavirus


2020 AGENDA CONFERENCE DAY TWO

  • Registration and welcome coffee from 07.30
  • Start of the Conference 08.30
  • Exhibition open from 08.00 to 19.00
  • Seated Lunch: 12.30

MORNING SESSIONS



 
Morning Chairman
Jean-Marc Uzé,
VP EMEA, Augtera Networks
USE CASE II Session
08.50
Proactive Network Troubleshooting Using Machine Learning
Showing how machine learning helped reduce from thousands of events to a handful of meaningful situations in their mobile backhaul network, and how machine learning helped reduce effort and improve customer satisfaction in a number of use cases, including when fibre cuts or power outages occur.

Cristian Panu, Expert Operations Engineer, Vodafone

Carsten Collatz, Senior Product Manager, Nokia
Smart Telemetry/Data Quality Session
09.10
How Many Data do we Need to Build a Good Classifier for Network Management?
Discussing how we can apply AI techniques to improve IP/MPLS Networks operations and user experience. Applying few-shot learning, meta-learning, and a generative algorithm to different domains of network management; eNodeB data analysis for quality assurance in mobile network, packet and flow data analysis for Web service identification of encrypted transport connections.

Kohei Shiomoto, Professor, Tokyo City University

Kohei Shiomoto is a Professor, Tokyo City University, where he is engaged in Research and Education in Network Management for the Internet, Mobile, and Cloud. Before joining Tokyo City University as Full Professor, he spent 28 years in NTT laboratories and was engaged in advanced research on SDN/NFV and Network Analytics, Communication Traffic & Service Quality, Traffic Engineering, IP and Optical Networking, (network architecture, IETF standardization, multi-layer traffic engineering), architecture design for high-speed IP/MPLS label switching router, IP router design, routing algorithm, and IETF GMPLS standardization, development of commercial ATM switching systems, research of high-speed networking technologies including ATM traffic control, measurement-based admission control, and ATM switch design.   From 1996 to 1997, he was on leave from NTT to join Department of Computer Science and Engineering, Washington University in St. Louis, MO, USA as Visiting Researcher and was engaged in research of high-speed networking technologies including dynamic flow switching and soft-state ATM switching.   He received the B.E., M.E., and Ph.D degrees in information and computer sciences from Osaka University, Osaka in 1987 1989, and 1998, respectively.

09.30
Intent Based Analytics
Talking about IBA - Intent Based Analytics (smart telemetry) - Analytics that are defined and derived from user intent and used to validate the intended state and are immediately actionable.
This is as opposite to “dump telemetry”, trying to get as much data as possible and then doing nothing with it, since it is too late and lacks context (un-actionable data).

Jeff Tantsura, Head of Networking Strategy, Apstra
09.50
ML/AI to Collect and Correlate Data from your Network and the Internet
In order to get a full perspective on one’s network, one must also keep in mind the ‘bigger picture’ of the internet and correlate its big data with the big data from their own network. Examining the idea behind matching and correlating these data sets and advanced ML/AI techniques that can be used to automate data collection and correlation.

Craig Labovitz, CTO, Deepfield Business Unit, Nokia
Reinforcement Learning Session
10.10
Reinforcement Learning for Telecommunication Network: from Opportunistic Spectrum Access to IoTs
In reinforcement learning, an agent chooses actions in order to maximize the rewards given by a dynamic environment. As the environment is initially unknown, the agent has to interact with it to gather information. Moreover, only the reward of the chosen actions is revealed. That is why the agent faces the exploration/exploitation dilemma: he has to explore loosely estimated actions in order to build a better estimate, and he would like to maximize his cumulated reward by playing the empirically best actions.

Raphaël Féraud, Research Engineer, Orange Labs

Raphaël Féraud received his Ph.D from the university of Rennes in 1997. As a research engineer of Orange, he has worked on various use cases of Artificial Intelligence: image processing, and specifically on face detection, dynamic allocation of resources for telecommunication networks, targeting of Internet advertising, churn, fraud detection, marketing optimization…  He led research projects on machine learning and Big Data. Since 2012, his research focuses on online learning, reinforcement learning and multi-armed bandits.

10.30
Coffee Break / Exhibition / Interop Showcase

11.00
Self-Explaining Adaptive Networks
Describing a model-free Reinforcement Learning based algorithms allowing to hide the inherent complexity of the environment and adapt to its changing conditions. These model-free approaches need to exploit the available structural knowledge and integrate with causal inference disciplines.

Armen Aghasaryan, Nokia Bell Labs
11.20
Machine Learning for Wireless Communications
Mobile cellular networks are becoming increasingly complex to manage while classical deployment/optimization techniques are cost-ineffective and thus seen as stop gaps. Discussing through various examples the on-going AI architectures and algorithms for the design of Next Generation Intelligent Networks.

Prof. Mérouane Debbah, IEEE Fellow, CentraleSupélec, Huawei
11.40
Increasing Network and Service Automation with Artificial Intelligence and Machine Learning
Presenting the ZSM architecture and the services it provides to enable and use Artificial Intelligence and Machine Learning to achieve secure, end-to-end, cross-domain service orchestration and automation.

Nurit Sprecher, ETSI ZSM ISG WG Vice-Chair
12.00 Panel
Next Frontiers in AI Networks
Moderator
Tilly Gilbert, Consultant, STL Partners

Tilly is a consultant at STL Partners. She works on a range of client projects with a particular focus on helping telcos squeeze the business potential from artificial intelligence and data analytics.   She has a BA in English Language and Literature from Oxford University and an MA in English Literature from the University of Pennsylvania.


Prof. Mérouane Debbah, IEEE Fellow, CentraleSupélec, Huawei

Rahul Aggarwal, Founder & CEO, Augtera Networks

Loutfi Nuaymi, Professor, IMT Atlantique
12.30
Seated Lunch

AFTERNOON SESSIONS



 
Afternoon Chairman
Jean-Marc Uzé,
VP EMEA, Augtera Networks
Self Healing Networks Session
14.00
What is Self Healing Enterprise and how to Become One?
Talking about how self-healing enterprise, level of self-healing and how autonomous IT enables self-healing.
Business benefits of self-healing are elevated digital user experience, optimization of IT resources, and achieve uninterrupted operations for the enterprises.

Paddy Padmanabhan, Founder & CEO, Appnomic Systems
14.30
Intent-based Intelligence: Systematic Self-healing Network
To support service agility, the network must evolve from a static resource system to a flexible and dynamic system that can meet business objectives. With the global network status control, a closed-loop network can be automatically built and maintained based on human service intentions to implement intelligent and systematic self-healing networks.

Christopher Mulley, Principal Architect of CTO Group, ZTE Corporation

Chris Mulley is a Principal Architect in the CTO Group of ZTE Corporation’s Integrated Solutions department. Chris is responsible for the 5G architecture focusing on core and transmission network technologies that feed into the development of cost effective end-to-end solutions, targeted at major global telecom operators.  A key part of this role involves informing a corporate strategic approach to the development of technology that enable the deployment of 5G services that meet network operator’s requirements and revenue generation. This included network transformation from traditional appliance based equipment architecture to more flexible deployments based on evolving SDN and NFV architectures. This strategy is aimed at enabling network operators and service providers to leverage these technology in order to develop new business models and revenue streams, and cost reductions through improved operational efficiency.  Chris’ specializes in the following areas:
• Transmission network solutions; • Core network solutions; • SDN and NFV; • 5G Security   Prior to working for ZTE Corporation, Chris has worked for a number telecom equipment vendors in product development and management roles, related to transmission network technologies.  Chris holds a BEng in Electrical and Electronic Engineering from Polytechnic of Central London. He is a member of IET.

15.00
Coffee Break / Exhibition / Interop Showcase

15.30
AI Chips and Intelligent Lossless Algorithms
Enabling zero packet loss on the Ethernet, unleashing the full computing potential of AI, and realizing the integration of computation, storage, and communication on DCNs:
  • Congestion-caused packet loss on traditional Ethernet becoming the bottleneck for improving computing power in the AI era: a packet loss rate of 0.1% resulting in a decrease of 50% in computing power
  • AI-based intelligent plane for DCNs, realizing zero packet loss

Xiaofeng Yang, Data Center Network Senior Architect, Huawei

Mr.Yang has 15-year experience in telecom carrier network, in charge of the research ,innovation, standard promotion work of data center network.   He and his team are taking an active part in the data center network solution innovation, esp in innovative lossless network and its related applicable scenarios research including AI computing cluster and distributed storage, SDN automation innovation and applicable network practice and on-going promotion, etc.

16.00
End of Conference Day Two Track 3
16.30
End of Conference Day Two Track 3