Standards and architecture approaches for ML in future networks - - PowerPoint PPT Presentation

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Standards and architecture approaches for ML in future networks - - PowerPoint PPT Presentation

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Regional Forum on Emerging Technologies Standards and architecture approaches for ML in future networks Place: Tunis Date: 22 April 2019 Presenter : Vishnu Ram OV (ITU T FG ML5G) ITU Regional Forum on Emergent Technologies Tunis - Tunisia,

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Regional Forum on Emerging Technologies

Presenter : Vishnu Ram OV (ITU T FG ML5G)

ITU Regional Forum on Emergent Technologies Tunis - Tunisia, 23-24 April 2019

Place: Tunis Date: 22 April 2019

Standards and architecture approaches for ML in future networks

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  • ITU T FG ML5G: intro
  • Use cases and Benefits
  • “Under the hood”: research options
  • Call for action! What can we do together?
  • FG ML5G Student projects

Agenda

2 ITU Regional Forum on Emergent Technologies Tunis - Tunisia, 23-24 April 2019

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ITU-T Y.3172 “Architectural framework for machine learning in future networks including IMT-2020” was consented on Victoria Falls, 4-14 March 2019, with support from multiple countries. Next meeting of FG in Geneva, 18 - 20 June 2019

  • ITU-T focus group Machine Learning for Future Networks including 5G (FG

ML5G) was established by ITU-T Study Group 13 at its meeting in Geneva (6-17 November 2017).

  • WG1: Many use cases (e.g., troubleshooting of network problems, drones,

self-healing, resource allocation for slices).

  • WG2: ongoing work for data handling and data models for ML in 5G networks.
  • WG3: ongoing work for ML intelligence levels, ML marketplace integration.

ITU T FG ML5G

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(from 3GPP TS 23.501 System Architecture for the 5G System)

Use cases-1: ML for 5G network optimization

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  • Data from different parts
  • f the network is used for

correlation, prediction and troubleshooting of problems.

  • Network or slice design

recommendations can be made based on ML.

  • Can lead to better user

experience and operator benefits.

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“Under the hood”

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Manage ment Plane NF NF AF ML Underlay SRC SINK ML Overlay

  • Interoperable, plugin architecture for ML
  • n various types of networks.
  • Adaptive framework for ML.

Overlay can evolve independent of the ML underlay.

  • Unstructured data may be input.

Symbol for ITU T Y.3172 ML Pipeline

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What can we do together? (Work items)

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Data handling techniques ML marketplace integration Sandbox, Testbeds

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Use cases-2: ML for real time prediction at edge

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  • Data from edge is used for

real time prediction, can assist MEC in decisions.

  • DL models are used for

predictions.

  • DL Models are deployed in

the edge where it is closer to the data. Edge Network

(ITU T Q.5001, ETSI MEC, 3GPP 23.501)

Core Cloud SRC SINK

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“Under the hood”

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Manage ment Plane NF NF AF ML Underlay SRC SINK ML Overlay

  • Declarative mechanism for ML

use case specification.

  • Enabling zero-touch ML service

in future networks. Plug in of data source (e.g. IoT) is supported.

  • Distributed instances of ML

pipeline across levels of network, with chained models. Symbol for ITU T Y.3172 ML Pipeline MLFO ML Intents

DM DM DM

MLFO: ML Function orchestrator DM: Data Model

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What can we do together? (ecosystem)

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ITU T FG ML5G Student projects!!

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  • FG ML5G is offering projects for students in the area of ML in 5G.
  • Student focussed:

○ Select problem statements which are relevant for the technical areas related to ML in IMT 2020. ○ Use guidance from a wide network of experts in the FG. ○ Make friends across the globe. ○ Get a (shiny) certificate at the end of successful completion of the project.

  • A list of 20 projects are available in ML5G-I-144R2
  • 4 countries participating currently (India, Brazil, Nigeria and Zambia)
  • How to join?

○ Send mail to vishnu.n@ieee.org ○ Join the ITU mailing list fgml5g-students

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References

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  • Use cases document from FG ML5G

https://extranet.itu.int/sites/itu-t/focusgroups/ML5G/input/ML5G-I-118-R9.docx?d=wc3704ffae74f 4bc58291b82ad52aae1c

  • Data handling framework document from FG ML5G

https://extranet.itu.int/sites/itu-t/focusgroups/ML5G/input/ML5G-I-148.docx?d=w586c00bd18f54a 10a2a976bb048ea512

  • ML marketplace integration document from FG ML5G

https://extranet.itu.int/sites/itu-t/focusgroups/ML5G/input/ML5G-I-146-R1.docx?d=w062a509012 3342af832d3cde0d9c8bea

  • Contact: vishnu.n@ieee.org
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Thank you

ITU Regional Forum on Emergent Technologies Tunis - Tunisia, 23-24 April 2019