Dr.-Ing. Leonardo Gomes Baltar (leo.baltar@intel.com)Senior Standards and Research Engineer

with inputs from Dario Sabella, Soo Jin Tan and Prakash Kartha

Virtual Worlds

Artificialintelligence

5gnetworks

AutonomousDriving

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At IntelWe’re powering the future of computing and communications,

delivering experiences once thought to be impossible.

Intel technology leadership

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Deliver the best customer experiences on the planet

Make the world’sbest semiconductors

Lead the Artificial intelligence& Autonomous revolution

Be the Leading end to end platformprovider for the new data world

Co-optimized process and

product design

CPU

FPGA SoC

MEMORY

Semiconductor leadership enablesPlatform leadership

Co-optimized products

MODEM

Intel’s Integrated Device Manufacturer model is foundational to delivering best-in-class platforms

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Devices/edge NETWORK Cloud/Data center

Intel delivers end to end Platforms

Software

4g/5G

MemOry

CUSTOM

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powering AI computing from edge to cloudCombining Intel hardware and software to accelerate AI

workloads for data-intensive tasks like autonomous driving

Devices / edge network Cloud/data center

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Contents

• Motivation

• What is Edge Computing?

• Examples of Edge Computing in road ITS

• In-Vehicle and City Experiences– MWC 2018

• Smart RSU example – MWC 2019

• Edge Computing standardization and ecosystem

• ETSI ISG MEC

• 3GPP

• 5GAA

• AECC

• Challenges

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Transformation of Automotive Industry …Transformation of Automotive Industry in Upcoming Decades

Advances in electronic and computing opened new transportation opportunities

Automotive sector transforms to deliver safe, green and intelligent transportation with ultimate goal to enable self-driving cars which are becoming reality

Evolution of Human Transportation

Outlook or FantasyHistory

RealityOngoing Transformation

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…Toward a data driven eraAdditional Component

• Cellular communication

Future automated driving is to be further

empowered by cellular communication

technologies

Practical Challenges

Human sensing / control capability

Environment perception through sensors: cameras, radar, LIDAR, and centralized processing of sensor data to control vehicle behavior

Real time massive data processing

Parallel / sequential processing

Core Technology Components

Artificial intelligence

Sense / fuse / decide

High-end computing capabilities

Latency / big data / throughput (computing and memory advances)

Precise location / navigation

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Automated and Connected cars – key driversConnected Car Vision

Cloud V2X services

Over the air updates

Infotainment / media delivery

Intelligent route and path planning

Tracking / fleet management

Transportation as a service

Inter-Car Communication

Vehicles talk to another cars, pedestrians, road side units

Road safety

Telematics information exchange

Environment perception

Cooperative & automated driving

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TO IMPROVE SERVICECAPABILITIES

OptimizeTCO

Comply with DataLocality

And reduce applicationLatency

EDGE COMPUTING IS THE PLACEMENT OFDATA CENTER-GRADE NETWORK,COMPUTE & STORAGE

ENDPOINTDEVICESCloser to

The EdgeIs the

BEFORE TRANSITIONTO THE ENDPOINT

ORAnother Network

Outmostlayers of

Processingor Network

WHAT IS EDGE COMPUTING?

Devices /Things

MANUFACTURING

TRANSPORTATION

ENERGY

VIDEO

HEALTHCARE

RETAIL

NetworkCore

Data Center|Cloud

On-premises edge

DRONES

PHONES

SMARTCITIESPCs

Network edge

WIRELESS ACCESSBASESTATIONS &

RAN

NEXT GEN CENTRAL OFFICE

(vEPC, vBNG)

EDGE DATA

CENTERS

CUSTOMER PREMISES EQUIPMENT

(uCPE, SD-WAN, EDGE COMPUTE OR FOG NODES)

SMALL CELLS LICENSED &

UNLICENSED

WIRELINEFIXED ACCESS(vCCAP, PON)

Driver for edgeLatency, bandwidth,

Security, connectivity

Edge Services on different types of Edge Platforms –> On-Premises and In-Network(uCPE, vRAN, NGCO, Edge Compute Nodes, and others)

Varies <1 ms <5 ms <10-40 ms < 60 ms ~100 msLatency expectation

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DATA WORKLOADS DRIVE EDGE COMPUTING

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Market Forecasts

Distributed Cloud unlocks 25% of the

5G operator revenue potential (*)

(*) Source: Ericsson study on 5G business potential

• MEC incorporates the benefits of virtualization and cloud-computing in order to

place high-powered computing capabilities as close as possible to subscribers.

• The largest number of installations, according to iGR (2017), will be for retail and

health care and social assistance. And this forecast was still not considering other

emerging verticals (e.g. VR/AR, automotive, industrial automation, …)

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MEC KPIs and their impact on business1. Latency improvement

2. Network utilization and cost savings

3. Energy efficiency, TCO analysis

4. Computational and Networking resources

• Also importantly, performance metrics are applications-specific as they are tailored

to vertical segments (e.g., automotive, industrial automation, VR/ AR etc.).

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• Motivation for these KPIs comes from

e.g. current positioning of operators (*)

(*) A. Manzalini , “Multi-access Edge Computing: Decoupling IaaS-PaaS for enabling new global ecosystems”, Berlin 19-20 Sept 2018, Edge Computing Congress, 2018

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• Performance assessment of MEC is key.

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Where is the edge? MEC performance should be compared against different deployment options

MEC gains depends also on the vertical / use case

Web

Access Level

RRH

RRH

RRH

macro

micro

BBU

micro

Local/Regional Level

National Level

Remote Cloud

app

app

app

app

app

app

app

Global Level

1x 10x10x 100x100x 1000x> 10000x

Industrial automation

Connectedvehicles

E-Healthdevices

VR/AR devices

Scale

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Advanced V2X & Edge Computing – MWC 2019 DEMO

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CPU Storage NetworkingIntel® Movidius™ Myriad™ X VPU

(optional)

Intel® Open NESS (optional)

Next Gen V2X

AnalyticsV2XAPPOthers

MEC Controller

Intel® Movidius™ Myriad™ X VPU

(optional)

Intel® Open NESS (coming soon)

Others

High Level PoC Architecture

Smart RSU PoC SW Architecture

Next Gen V2X on Intel

Atom™ IVI System

Next Gen V2X on Intel® Xeon® D

Processor PlatformCloud

Car Unit Smart RSU Cloud

Sidelink OTA

OpenVINO™ toolkit

Architecture Overview – MWC 2019 DEMO

More on Open NESS at www.open-ness.org

Key features

V2V, V2P, V2I radio links based on 5G NR

technology

Test chip with integrated communication modem

and neural network capabilities

MEC and FlexRAN for network infrastructure

Neighborhood vehicles and environment as

compute/storage nodes to form dynamic local

cloud

Enable new wave of time sensitive and local

relevance service in addition to V2X usages

Next Gen V2X Wireless Test Platform – MWC 2019 Demo

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ETSI ISG Multi-Access Edge Computing (MEC)

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End 2016

ETSI MEC phase 1 ETSI MEC phase 2

End 2014

• MEC technology - previously Mobile-Edge Computing – offers IT service and Cloud computing capabilities at the edge of the network

• Develops specifications that will allow the hosting of third-party applications in a multi-vendor Multi-Access Edge Computing (MEC) environment and accelerating the development of edge applications across the industry, to increase market scale and improve market economics

• By shifting processing power away from remote data centers and closer to the end user, it enables an environment that is characterized by proximity and ultra-low latency, and provides exposure to real-time network and context information

ETSI ISG Multi-Access Edge Computing (MEC)

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End 2016

ETSI MEC phase 1 ETSI MEC phase 2

End 2014

• Phase 1 - Platform Service API specifications, such as Application Enablement, Radio Network Information Service, Location Service, User Equipment Identity Service, Bandwidth Management Service and User Equipment Application Enablement

• Phase 2 - New use cases and requirements to address topics such as charging, regulatory compliance, support of mobility, support of containers, support of non-3GPP mobile and fixed networks, slicing, 3GPP 5G MEC integration, testing, and key vertical use cases such as automotive. Integration with ETSI’s ISG on Network Functions Virtualisation (NFV)

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ETSI MEC standard work on V2X• MEC GR-022 - support for V2X use cases

Focuses on identifying the necessary MEC support for V2X applications

Collects and analyze the relevant V2X use cases (e.g., the from external organizations.)

And evaluate the gaps from the defined MEC features and functions, by identifying the new requirements including new features and functions

• MEC GS-030 - V2X service API

Introduces new MEC Service, V2X Information Service (VIS) based on the study report conclusions in MEC GR 022

Support for service exposure and communication ability across participating V2X applications in different MEC systems

Expose PC5 interface configuration parameters of one system to another system (the right-hand side figure is showing a relevant multi-operator scenario)

Edge computing in 3GPP

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• 3GPP has adopted the Edge Computing concept as part of their 5G architecture • 3GPP TS 23.501 (Clause 5.13) on the architecture for 5G Systems,

contains a set of new functional enablers for the integration of MEC in 5G networks.

• 3GPP is also developing the API framework for the northbound APIs, taking into account corresponding ETSI ISG MEC APIs

• ETSI White Paper No. 28 “MEC in 5G networks”• Focuses primarily on exploring edge computing enablers from 3GPP

and on how the 3GPP ecosystem may benefit from the MEC system and its APIs, as a set of complementary capabilities to enable applications and services environments at the edge of mobile networks

5G Automotive Association – 5GAA

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5G Automotive Association

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5G Automotive Association• Edge Computing as priority area

• White paper: “Toward fully connected vehicles: Edge computing for advanced automotive communications” available at www.5gaa.org

• Covering use cases, business models, standardization and ecosystem

• Cooperation agreement with ETSI

• Particular interest in collaboration with ETSI ITS and ETSI MEC

• More to come in the near future....

• New Work Items on key areas such as MEC and VRU

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Automotive Edge Computing Consortium - AECC

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Network/Computing for Automotive BIG DATA

To accommodate the automotive big data in a

smart and efficient fashion.

Global andSustainable Ecosystem

The next generation connected cars will require

improved systems in order to evolve.

Initial Focuson Vehicle to Cloud

The context is the high volume Vehicle to Cloud

services and not the classical V2X/C-ITS services with an initial focus on automated

vehicles

Leading Market Actors Join Forces

Toyota, Toyota ITC, Ericsson, Intel, Denso, DOCOMO, KDDI,

NTT are funding members and more already joined or

are in the pipe to join

Automotive service evolution needs BIG DATA and its infrastructure

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AECC Vision and ChallengesITS

IVI BIG DATA• Cloud (downlink)• High Interactivity

• P2P (sidelink)• Low latency• High reachability

• Cloud (uplink)• Big data capacity• Delay tolerant

CELLULAR WiFi

Short Range CELLULAR V2X

CELLULAR

CHALLENGE!

SAFETY

USER EXPERIENCE CAPACITY

Evolution of• Network architectures• Computing infrastructures• Business models

Accommodate automotivedata & services• Smart and effective fashion• Multi-operator environment• Multi-edge environment

Challenge to get a homogenous service in a heterogeneous network

AECC – System-wide Service Requirements

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Source: AECC White Paper available at www.aecc.org

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Edge computing Challenges for Road ITS• Support and interoperability

• Multiple road and network infrastructures

• E.g. Multiple RSU and cellular network operators

• Multiple infrastructure vendors

• Multiple applications and service providers

• Multiple vehicle OEMs and suppliers

• Support global interoperability

• Effective incorporatio of AI enabling technologies

• Appropriate Radio Access Neworks

• Functional Safety Compliance

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“Don’t be encumbered by history, go off and do something wonderful.”Intel cofounder Bob Noyce

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