Towards Self Driven Networks / 2018년 4월 10-12일 / Marriott Paris
4월 10일(화)
4월 11일(수)
4월 12일(목)
기술 강좌
컨퍼런스 첫째날
컨퍼런스 둘째날
2018년 4월 12일(목)|컨퍼런스 둘째날

  • 07:30 등록, 커피
  • 09:00 컨퍼런스 둘째날 시작
  • 08:00-19:00 전시회 개최
  • 12:30 점심식사
  • 17:00 컨퍼런스 종료

Jean-Marc Uze Consultant
사례 연구와 서비스 프로바이더의 전략에 관한 세션
대규모 AI의 도입, 네트워크 가상화와 자동화
Looking at how specific AI techniques, combined with an abstracted network model, can solve real world issues related to optimization and automation at scale in multi-layer, multi-vendor networks. In particular, how this combination ultimately delivers the vision of adaptable, dynamic, intelligent, business-driven networks based on SDN and NFV. Discussing case studies and lessons learned from real world projects with global network operators.

Robert Curran,
Strategic Marketing, Aria Networks
인텐트 드리븐(Intent-driven), 코그니티브 네트워크의 실현 방안
Managing communication networks will never be a trivial task, however it does not have to remain as complex as it is today. Designing, developing and deploying innovative technologies in the realm of Intent-Driven Networking will generate enormous gains in performance (doing things better and faster) and in functionality (enabling things previously impossible). But the task will not be easy. This talk will highlight the main challenges ahead and the key enablers in the realization of this vision of future networks. The presentation will make a synthesis of definitions and elements composing an archetypal solution for intent-driven networks by analyzing the work in standards, open source and research initiatives. Finally, an applicability to an IoT use case will illustrate some of the concepts developed in the talk.

Laurent Ciavaglia, Senior Research Manager, Nokia, Bell Labs
BT의 AI 전략

Prof. Dr
Detlef Nauck, Chief Research Scientist for Data Science, BT
휴식시간/전시회/관련 이벤트
AI와 IoT에 관한 세션
새떼 모방:AI 기술을 이용한 IoT의 대규모 보안 대책
Fortunately, IoT devices are not like humans, the vast majority of IoT devices are/will be simple, single-minded, and generally predictable. The problem is how to monitor and learn each of those IoT devices, or rather classes and types of IoT devices. Fortunately #2, IoT devices are more like flocks of birds. They move in large groups in the same direction, although unlike flocks of birds, they rarely make sudden changes in their direction or behavior.
Analytics and machine learning enhanced security of IoT networks is like an ornithologist watching flocks of birds: observe, identify, predict, and protect.

Steve Kohalmi,
Mobile Network Security Architect, Office of the CTO,
Juniper Networks

11.30 패널 디스커션
IoT와 5G를 위한 AI:기술과 아키텍처 문제
Dean Bubley,
Disruptive Analysis


네트워크 분석과 텔레메트리에 관한 세션
인사이트 드리븐 자동화 네트워크
Describing a solutions that provides visibility and control that allows to respond to traffic dynamics and security threats. This new operational model uses the enhanced packet intelligence and control capabilities of the groundbreaking FP4 routing silicon. It lets you build a smart network fabric that supports granular traffic management, scalable flow optimization, and highly effective in-line DDoS mitigation.

Roland Thienpont,
IP Division Product Manager, Nokia
네트워크 텔레메트리:빅데이터 분석의 기반
Introducing telemetry, a new technology for freeing network data. Discussing the origins and applications of telemetry, some hard-won lessons and the eco-system of open-source and commercial tools that enable you to turn data into insights. Telemetry brings speed and scale to network monitoring, transforming the landscape into a big data analytics playground.

Kumar Reddy,
Director, Technical Marketing Engineering, Cisco

Kumar Reddy is Senior Director in charge of SP Network Software and Automation architecture. He is responsible for driving new software technology and products around IOS-XR.

휴식시간/전시회/관련 이벤트
Analytics Edge의 기반과 Lambda@Edge 기반 애플리케이션 레이어
Sharing results on analytics-edge based underlay awareness for minimizing latency/loss maximizing capacity.
As well as lambda-edge based application layer deep analytics.

Sharon Barkai,
완전 자동화 분석 기능의 실현 방안
Considering how we can efficiently build pipelines for network data analytics, that enable us to apply advanced analytics at scale with zero-touch. Presenting real-world use cases to illustrate how this can be achieved, using open source software to dynamically analyse telemetry data and provide insights in real-time.

John Evans, Distinguished Engineer, Cisco

John is a Distinguished Engineering at Cisco, focussed on network and technology transformation; defining what network architectures will look like post the transformation to cloud-based services, virtualisation, SDx, NFV, IOT and Big Data Analytics.

16.30 클로징 패널 디스커션
이론, 연구, 발전
What has been realised
What remains to be done
What are the perspectives


Dean Bubley,
Disruptive Analysis

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