Post on 14-Mar-2020
NXP and the NXP logo are trademarks of NXP B.V. All other product or service names are the property of their respective owners. © 2017 NXP B.V.PUBLIC
SEPTEMBER 24TH, 2019
DR. RAJEEV ROY, NXPMICHAEL JOHNSTON, NXP
FROM THE CLOUD TO THE CAR:THE END TO END PICTURE
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AGENDA• Market trends• Use cases• Network evolution and landscape• Security considerations• Vehicle telematics• Summary
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Automotive Industry Megatrends
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V E H I C L E B I G D ATAo p p o r t u n i t i e s
MILLION
Represents global dataSources: *Strategy Analytics, 2019; **ABI Research, 2018
Shipped in 2018* Vehicle data generated per hour**
TERABYTES4+ VEHICLE DATACONNECTED VEHICLES
Connected vehicle penetration*
50%2019
2025
40% 73%2018 2025
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Vehicle Data Opportunities Will Transform the Automotive Industry
New Revenue StreamsUp to $750B* for data-driven services by 203077.4% millennials** willing to pay for updates
Enhanced Safety and SecurityFault detection & notificationIntrusion detection and preventionCrash detection / emergency response
Improved User ExperiencesPersonalization, comfort and conveniencePost-sale feature upgradesLocation-based services
Reduced CostsPredictive maintenanceReduced warranty / recall exposureFleet management
Sources: McKinsey & Company, Monetizing Car Data, 2016; IHS Markit forecast, 2018
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Use cases
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Over-The-Air (OTA) use case
• Over-the-Air firmware/software updates is a key trend in the industry
• Trend to move OTA Management function in Gateway ECU− Centralized management of OTA deployment in-vehicle− Interface to OEM servers − Security is paramount
• Utilizing OTA mechanism to deploy new features via SW in field (Agile SW deployment)− Build performance overhead into hardware− In-field, test & deploy new customer features as use cases
emerge
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Automotive SDN use case • Central configuration of data-plane
switches in IVN−Support both TSN and BE traffic−Support switching and routing
• Use cases:−Dynamic network changes E.g. Adding new services via OTA while
maintaining optimum network efficiency −Error handling E.g. Fast failover
• NETCONF CNC example:
Data path
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Analytics Typical use cases (1)
• Predictive maintenance− Identify vehicle maintenance issues before they
occur − Schedule maintenance when needed− Quickly identify the root cause of any problem− Machine Learning (ML) at the edge to detect
safety relevant maintenance issues
• Intrusion Detection and Prevention (IDPS)− Uses anomaly detection techniques to identify malicious
activity or faults on vehicle networks− Detects static anomalies (non ML)− Contextual anomaly – ML based− ML at the edge to detect attacks in real time
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• Crash detection− Used to detect if a crash occurs− Indicates the severity of crash− Indicates likelihood of serious injury− Capture moments before crash− ML at the edge to detect crash real time
• Usage based insurance− Behaviour policy pricing− Premium based on driver use of vehicle− ML determine driver premium depending on
several risk factors− ML at the edge to detect driver and usage
Analytics Typical use cases (2)
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Predictive DataAnalytics
Analytics: Handling Data• On-Vehicle processing
− Capture: Data to service (raw data to speed, temp, etc) Data logging
− Process: Predictive data analytics (limited)
• Deviation detection • Signal correlation, comparison to reference modules
Aggregate Diagnostic Trouble Codes (DTC) with other data and time stamps
− Share: Compression before offload
• Off-Vehicle Cloud processing− Correlation of data across multiple vehicles− Advanced predictions using historical and warranty
data− Part defect history
SOCCloud
NetworkServices
On board data streams
On board data streams (sensor data)
Repair history
Aggregated vehicle data
Model data
Model data (limited)
Off-VehicleOn-Vehicle
Predictive Data Analytics
ShareProcessCapture
Hardware support to analyse network
streams
Heavy math vs Decision Tree
Optimize available
bandwidth
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Network evolution and landscape
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Ethernet Ecosystem
Courtesy: Ethernet AllianceNote: Original image (link) is modified to have less text
The vehicle as a part of the larger Ethernet Ecosystem
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From LAN to WAN to IVN
Access Aggregation/Edge Metro/Core-Edge
Residential
Enterprise
Mobile
xDSL ATM
PDH
PDH/Frame Relay
IP/MPLS
ATM
SDH
TransportPDH
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From LAN to WAN to IVN
Access Aggregation/Edge Metro/Core-Edge
Residential
Enterprise
Mobile
xDSL
Ethernet
IP/MPLS
ATM
SDH
Transport
Ethernet
Ethernet
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From LAN to WAN to IVN
Access Aggregation/Edge Metro/Core-Edge
Residential
Enterprise
Mobile
xDSL
IP/MPLS
Ethernet
SDH
Transport
Ethernet
Ethernet
Ethernet
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From LAN to WAN to IVN
Access Aggregation/Edge Metro/Core-Edge
Residential
Enterprise
Mobile
IP/MPLS
Ethernet
OTN
Transport
Ethernet
Ethernet
EthernetProvider Backbone
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From LAN to WAN to IVN
Access Aggregation/Edge Metro/Core-Edge
Residential
Enterprise
Mobile
IP/MPLS
Ethernet
OTN
Transport
Ethernet
Ethernet
EthernetProvider Backbone
WiFi
Wired
Mobile
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Day in the life of a packet – A typical infra view
OEM Data Center Access Edge/Provider Backbone Edge/Provider Access Mobile RadioAccess
Vehicle Wireless Gateway
Application
TCP/UDP
IP
C-ETH C-ETH
S-ETH
B-ETHMPLS
OTN
B-ETH
IP
C-ETH
S-ETH
IP IPGTP/PDCP
UDP/IPRLC
IPPDCP
UDP/IPRLC
Application
TCP/UDP
IP
Target ECU
Copper Copper Copper CopperOptical CopperRadio
TCP: Transmission Control ProtocolUDP: User Datagram ProtocolIP: Internet ProtocolC/S/B-ETH: Customer/Service/Backbone EthernetMPLS: Multi Protocol Label SwitchingOTN: Optical Transport NetworkGTP: GPRS Tunneling ProtocolPDCP: Packet Data Convergence ProtocolRLC: Radio Link Control
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Wireless Connectivity Landscape
Ultra-short Range
Short Range
Wide Range
CAT-M1 NB-IoT5G
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Evolution of the Cellular Base Station
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Security considerations
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Secure Comms
WAN0
WAN1LAN0
Telematics Control Unit
(TCU) Gateway
LAN0
Subnet 192.168.4.x
Subnet 192.168.3.x
Subnet 192.168.2.x
88.11.10.11
78.14.10.19
OEM Server
VLAN1
VLAN2
VLAN3
VLAN4
APP
TLS
TCP
IP
Ethernet
IP
Ethernet
IPsec
APP
TLS
TCP
IP
Ethernet
IPsec
MACSEC MACSEC
IPsec and TLS can both be end to end
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Vehicle telematics
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Internal vehicle communications
Domain controller architecture Zonal architecture
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Example ECU architectures
Secure Ethernet Gateway
Telematics Control Unit (TCU)
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Summary
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Summary
• Market trends− Data is king!− Data volume, access and handling are key defining points
• Use cases− Enablement of new features is not a luxury, it’s something the user expects− OTA, SDN, remote diagnostics and analytics are key drivers
• Network evolution and landscape− Transport of a bit of data from the source to destination involves a myriad of technologies− 5G allows new levels of flexibility and scalability to enable new use cases− Ethernet is the common denominator
• Security considerations− A portfolio of techniques is available to protect data− End to end and/or point to point
• Vehicle telematics− Handling the data within the scope of the vehicle itself is non-trivial− TCU and Gateway ECUs are two of the key elements which complete this picture
PUBLIC 28© 2019 Cloudera, Inc. All rights reserved.
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NXP-CLOUDERA VEHICLE EDGE2AI ANALYTICS & MACHINE LEARNINGArchitecture for Unlocking the Value of Vehicle Data
ANALYZE7 •Self-Service Business Intelligence (BI)
•Fleet Analytics
LEARN8
• Historical vehicle data• Historical maintenance records• Historical usage characteristics• Historical failures
Model Inputs
9 DEPLOY
ENTERPRISE TRANSACTION DATA
Design, MFG, Dealer Service, Warranty, etc.
5
ENRICH
Connected Car 1 Connected Car NREAL-TIME
ACTION
ACT1 VEHICLE EDGE ANALYTICS
TRANSMIT2
ENTERPRISE DATA LAKE
3
4
6
CDF
D A T A I N M O T I O N
V E H I C L E S E R V I C E -
O R I E N T E DG A T E W A Y
STORE, ENRICH & PROCESS
CDH D A T A A T R E S T
C l o u d e r a D a t a S c i e n c e
W o r k b e n c h
LEARN
ANALYZE
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Thank you
NXP and the NXP logo are trademarks of NXP B.V. All other product or service names are the property of their respective owners. © 2017 NXP B.V.