A Practical Application of Monitoring data and AI for ...

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A Practical Application of Monitoring data and AI for Network Management in an Industrial Environment July 2021 Diego R. López – Telefónica Ignacio Domínguez, Daniel González - UPM

Transcript of A Practical Application of Monitoring data and AI for ...

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A Practical Application of Monitoring data and AI for Network Management in an Industrial Environment

July 2021Diego R. López – TelefónicaIgnacio Domínguez, Daniel González - UPM

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Slice B

Slice C

Slice A

Data center (hosting cloud)

Edge data center(hosting edge cloud)

5G End-to-End Infrastructure(Radio, Transport, Cloud)

Orchestrator

Radio

Industrial Applications

5G-Enabled Growth in Vertical Industries

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Orchestration

Mission of the Project: Automatically build, deploy and managedifferent vertical industrial services over a shared End-to-End 5Gsystem (incl. Application Domain, Infrastructure Domain, OrchestrationDomain), and perform real field trials validation and demonstrations

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• 5Growth aims to perform real field trialsinvolving customer sites of four vertical locations in Portugal, Spain and Italy

• This requires the development, installation, validation and testing of commercial 5G radio, transport and core technologies in vertical sites, connected with the ICT-17 platforms

• PilotsIndustry 4.0• INNOVALIA

• COMAU

Energy• EFACEC_E

Transportation• EFACEC_S

Pilots

3Energy

Transportation

Vertical premises

Vertical premises

5G EVE

Industry 4.0 Industry 4.0

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5Growth Innovation Focus

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Vertical Support

Monitoring Orchestration

Data Infrastructure

Control & Management (Closed-loop, AI/ML)

End-to-end orchestration

Smart Orchestration &

Control

Anomaly Detection

Forecasting and Inference

Security

CI/CD

Containerization

ü Smartness ü Flexibility ü Efficiency ü Automationü Performanceü Security Framework Architecture Algorithms

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Data Infrastructre

The Three-Dimensional Closed-Loop

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Closed-loops for the processes of

• Collecting monitoring data from the services and networks

• Performing real-time data analytics for identifying events to handle

• Making orchestration decisions for optimization and/or reconfiguration of the system.

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Digital Twin appInterface

Coordinates

Commands

EDGENETWORK

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Drivers

Motion planningControl

Use Case: Robotic Digital Twin

RAN

VNF 2 target latency: 60 ms

VNF 1target latency: 600 ms

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VNF

5Gr-RL

5Gr-VS

WIM

5Gr-SO

Mon

itorin

g

5Growth MANO and Monitoring

Model Execution

BarcelonaTorino Scalingoperation

Deployed Scenario

Heterogeneous WAN transport network

VNF VNF

VIM

Scalingoperation

VPN (data, control and management)

AI/ML Platform

YARN cluster manager

Spark

Interface Manager

BigDLRay

MLlib

AI/ML model register

AI/ML param. register

HDFS dataset storage

ML lifecycle Mng

Interface for model onboarding

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Monitoring jobs configuration

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3

AIML model upload and training

5Gr-Service Orchestrator 5Gr-VoMS 5Gr-AI/ML Platform5Gr-VS

Service request2

Deployment and Configuration

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Dataflow configuration4

Real-time performance metrics5

AIML model request/response6

Data consumption7

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Scaling workflow

Model execution and scaling triggering8

3 Monitoring jobs configuration

Topic configuration4

5 7 8

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• 5Growth addresses data-driven network management in a three-dimensional closed loop• The common double loop for learning and inference• An additional control loop for monitoring data flows

• Making use of the project data infrastructure• Data-driven requirements embedded in service descriptors• Monitoring orchestration• Model-based data flows

• Applied to a real industrial use case• A path to be explored for other classes of Digital Twins

Concluding

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• J. Baranda, J. Mangues, E. Zeydan, L. Vettori, R. Martínez, X. Li, A. Garcia-Saavedra, C. Fabiana Chiasserini, C. Casetti, K. Tomakh, O. Kolodiazhnyi, C. Jesus Bernardos: On the Integration of AI/ML-based scaling operations in the 5Growth platform, in Proceedings of the 6th IEEE Conference on Network Functions Virtualization and Software Defined Networking (IEEE NFV-SDN 2020), 9-12 November 2020.

• J. Baranda, J. Mangues, E. Zeydan, C. Casetti, C. Fabiana Chiasserini, M. Malinverno, C. Puligheddu, M. Groshev, C. Guimarães, K. Tomakh, D. Kucherenko, O. Kolodiaznnyi, Demo: AIML-as-a-Service for SLA management of a Digital Twin Virtual Network Service , in Proceedings of the International Conference on Computer Communications (IEEE INFOCOM), 10-13 May 2021.

• The whole use case demo on YouTube:• https://youtu.be/7V3AKSrWzzY (short)• https://youtu.be/K5GyrAD7h_Q (long)

More Can Be Found at…

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