Contents

1.Key Takeaways

2.Overview

3.Problem Statement

4.Survey Says-Current State of the Industry

5.Intelligent Networking Challenges

6.Feasibility

7.Next Steps and Recommended Actions

8.Conclusion and Call to Action

9.Extra Text

Revision History and control

Rev

Date

Author

Description

Reviewed

Approved by
v1027 Sept 2021Beth Cohen (Verizon)Edited for readability – Final Review Needed 

v0926 Sept 2021Beth Cohen (Verizon)Edited all the materials together

v0814 Sep 2021

Yuhan Zhang(CMCC)

Lingli Deng(CMCC)

Kaixi Liu(CMCC)

Revising the structure and content of the white paper

Adding recommendations for the intelligent networking transformation



V0717 Aug 2021Yuhan Zhang(CMCC)merged with v06

V0603 Aug 2021Beth Cohen (Verizon)Updates by Steve Casey (Verizon) Not merged with the work by Yuhan yes.

V0503 Aug 2021Yuhan Zhang(CMCC)

Recommendation for network intelligence testing and certification

EUAG Team

V04

20 Jul 2021Yuhan Zhang(CMCC)survey results, challengeEUAG Team

V03

24 May 2021

Massimo Banzi (TI)

Beth Cohen (Verizon)

Steve Casey (Verizon)

Definition sections, survey analysis

EUAG Team

Uploaded

V01

15Apr2021

Beth Cohen (Verizon)

Creation of original document and outline of paper.

EUAG Team


V02

13May2021

Beth Cohen (Verizon)

Outline with some text.  Asking for input from the EUAG Team

EUAG Team


White Paper Assumptions and Overall Objectives:

  • Audience: Technical and strategic leaders in the Telecom Industry interested in understanding the role of intelligent tools, AI and machine learning can have in support of their network infrastructure, customer .
  • 7-10 Pages in length total – possibly will be some separate related papers on specific use cases and other information that does not fit into this one
  • Do not declare or propose a definite solution just share EUAG Operator community point of view
  • Purpose of White Paper is to share information about EUAG member companies’ approaches to network intelligence

Paper Overview

  • Based on the findings of a LFN sponsored survey of over 60 operators and vendors in the telecom segment, demonstrate the current state of adoption of the AI/ML technology for operators.
  • Make recommendations for where Open Source communities should be focusing their resources to further the intelligent networking efforts.
  • Call to action: Market and executive orientation.  Purpose is to get people excited about Intelligent Networking as emerging technology and its importance, yet have an understanding of where the gaps are in both the technology and its adoption.. Bullet list of gaps.  2-3 bullet items.  Identify missing Open-Source tools and potential projects.

Survey - AI/ML Survey (Result & Analysis) 

@Yuhan Zhang Beth Cohen

Uploaded current version of paper


Table for contributors to white paper and status

Contributors/CSPs

Sections

Status

Comments

Beth Cohen

 (Verizon)

Section 1-9Created first draftPosted first draft to this page.  

Yuhan Zhang

(China Mobile)

Section 1-9



Lei Huang

(China Mobile)

Section 1-9
Created workspace in confluence page
TBA


Steve Casey (Verizon)TBA

Timeline

Work ItemsTime
Complete the paper final draftSep 13th,2021
EUAG review and final versionSep 17th,2021
Share a form paper MAC magicSep 24th,2021
PublicationOct 8th,2021
ONES Summit White Paper WebinarsOct & Nov,2021
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