building autonomous and connected vehicle systems with the vortex internet of things data sharing...
TRANSCRIPT
Building Autonomous and Connected Vehicle Systems with the
Vortex IoT Data Sharing Platform Angelo Corsaro, PhD Chief Technology Officer
HYPE CYCLE 2015
GARTNER
HYPE CYCLE 2015
GARTNER
HYPE CYCLE 2015
GARTNER
HYPE CYCLE 2015
GARTNER
What is IoT all About?
IoT is about extracting value through the insights derived from the real-time and historical
data produced by a cyber-physical system
— Data is the currency of IoT —
the buzZ
CIoT
Humanismdigital
smartcollar
connected f0rk
smart socks
Smart Lightbulbs
CIoT Platforms
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Cloud-Centric Architecture
Device-2-Cloud Communication
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the ValueIIoT
While consumer applications such as fitness monitors and self-driving cars attract the most attention and can create significant value, we estimate that B2B/Industrial applications can generate nearly 70 percent of potential value enabled by IoT.
THE INTERNET OF THINGS:
MAPPING THE VALUE BEYOND THE HYPE Mc Kinsey, June 2015
How is IIoT Different?
device-to-device communication
Latency Constraints
Autonomous Vehicles
coordination of fast moving autonomous vehicles
intermittent connectivity
dynamic pairing of devices
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Smart Factory0.5 TB of data
produced per day
Oil Rig 30000 data pointsonly 1% of available data
used today
CIoT / IIoT Differences
IIoT is concerned with reactive cyber-physical systems IIoT is about interacting with the physical world
Cloud-centric architectures centred around device-to-cloud communication are not
applicable/sufficient for IIoT applications because of performance, connectivity and
resource constraints
This essential difference introduces a series of requirements for IIoT platform
that are not addressed by device-2-cloud centric IoT platforms
Connected Autonomous Vehicles
l
Data Sharingneeds
Device-2-Devicecommunication
Device-2-Cloud connectivity is not always possible due to connectivity challenges, response time or data volumes
Location Transparency
Data should flow where needed transparently and independently from the location of its source
Vehicle diagnostics and sensor data should transparently flow where needed. For instance within the car for driving assistance and outside for preventive maintenance
Performance Transparency
Data flows should be dynamically adapted to deal with QoS/bandwidth differences across networks
The data that is sent across vehicles should be dynamically adjusted depending on the quality of the connection. Critical data should alleyways take priority!
Cloud + FogComputing
Cloud and Fog computing architectures should be transparently supported to allow for data to be processed wherever makes the most sense
Autonomous Vehicles
coordination of fast moving autonomous vehicles
intermittent connectivity
dynamic pairing of devices
DurabilityAlong with real-time data, historical data should be available for query and non-real-time analytics
Access to vehicle data must be secure!
Interoperability
Data sharing standard are a pre-prerequisite for IoT.
Without standards there is not interoperability, without interoperability there is not IoT
device-to-device communication
Latency Constraints
SecurityData-Level security should be provided to simplify the deployment of secure IoT systems
Access to vehicle data must be secure!
Vortex is a standard-based technology for efficient, ubiquitous, interoperable, secure, and platform independent data sharing across network connected devices
in131 Characters
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Proven in Defence / Aerospace
Integrated Modular Vetronics Training & Simulation Systems Naval Combat Systems
Air Traffic Control & Management Unmanned Air Vehicles Aerospace Applications
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Broad Commercial Applications
Agricultural Vehicle Systems
Train Control Systems Complex Medical Devices
Smart CitiesLarge Scale SCADA Systems
High Frequency Auto-Trading
Device-2-DeviceDevice-2-Cloud
Fog-2-Cloud
Device-2-Fog
Cloud-2-Cloud
Fog-2-Fog
Device implementations optimised for OT, IT and
consumer platforms
Native support for Cloud and Fog Computing Architectures
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VORTEX supports both the Cloud and the Fog Computing Paradigm
VORTEX natively supports:
- Device-to-Device Communication
- Device-to-Cloud Communication
Cloud, Fog and Edge Computing
Cloud Computing
Fog Computing
Device-to-Cloud Communication
Device-to-Device Communication
Fog-to-Cloud Communication
Cloud-to-Cloud Communication
Device-to-Device Communication
Collect | Store | Analyse | Share
Collect | Store | Analyse | Share
Fog Computing
Fog Computing
Available across IT, Consumer and OT platforms Device-2-DeviceDevice-2-Cloud
Fog-2-Cloud
Device-2-Fog
Cloud-2-Cloud
Fog-2-Fog
Polyglot and Interoperable across Programming
Languages Device-2-DeviceDevice-2-Cloud
Fog-2-Cloud
Device-2-Fog
Cloud-2-Cloud
Fog-2-Fog
Fully Independent of the Cloud Infrastructure
Device-2-DeviceDevice-2-Cloud
Fog-2-Cloud
Device-2-Fog
Cloud-2-Cloud
Fog-2-Fog
Private Clouds
Native Integration with the hottest real-time analytics
platforms and CEP Device-2-DeviceDevice-2-Cloud
Fog-2-Cloud
Device-2-Fog
Cloud-2-Cloud
Fog-2-Fog
Device-2-DeviceDevice-2-Cloud
Fog-2-Cloud
Device-2-Fog
Cloud-2-Cloud
Fog-2-Fog
High Performance
30 μs peer-to-peer latency
2.5M+ msgs/sec peer-to-peer throughput
Device-2-DeviceDevice-2-Cloud
Fog-2-Cloud
Device-2-Fog
Cloud-2-Cloud
Fog-2-Fog
High Performance
4 μs fog/cloud routing latency
Grasping the Idea
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Vortex provides a Distributed Data Space abstraction where applications can autonomously and asynchronously read and write data enjoying spatial and temporal decoupling
Its built-in dynamic discovery isolates applications from network topology and connectivity details
Vortex’ Data Space is decentralised
High Level Abstraction
DDS Global Data Space
...
Data Writer
Data Writer
Data Writer
Data Reader
Data Reader
Data Reader
Data Reader
Data Writer
TopicAQoS
TopicBQoS
TopicCQoS
TopicDQoS
Conceptual Model
DDS Global Data Space
...
Data Writer
Data Writer
Data Writer
Data Reader
Data Reader
Data Reader
Data Reader
Data Writer
TopicAQoS
TopicBQoS
TopicCQoS
TopicDQoS
Conceptual Model Actual Implementation
Data Writer
Data Writer
Data Writer
Data Reader
Data Reader
Data Reader
Data Writer
TopicAQoS
TopicBQoS
TopicCQoS
TopicDQoS
TopicDQoS
TopicDQoS
TopicAQoS
DDS Global Data Space
...
Data Writer
Data Writer
Data Writer
Data Reader
Data Reader
Data Reader
Data Reader
Data Writer
TopicAQoS
TopicBQoS
TopicCQoS
TopicDQoS
The communication between the DataWriter and matching DataReaders can be peer-‐to-‐peer exploiting UDP/IP (Unicast and Multicast)or TCP/IP
Data Writer
Data Writer
Data Writer
Data Reader
Data Reader
Data Reader
Data Writer
TopicAQoS
TopicBQoS
TopicCQoS
TopicDQoS
TopicDQoS
TopicDQoS
TopicAQoS
The communication between the DataWriter and matching DataReaders can be “brokered” but still exploiting UDP/IP (Unicast and Multicast)or TCP/IP
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Abstracting Connectivity
Cloud Computing
Fog Computing
Device-to-Cloud Communication
Device-to-Device Communication
Fog-to-Cloud Communication
Cloud-to-Cloud Communication
Device-to-Device Communication
Collect | Store | Analyse | Share
Collect | Store | Analyse | Share
Fog Computing
Fog Computing
Autonomous Vehicles
coordination of fast moving autonomous vehicles
intermittent connectivity
dynamic pairing of devices
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A Topic defines a domain-wide information’s class
A Topic is defined by means of a (name, type, qos) tuple, where
• name: identifies the topic within the domain
• type: is the programming language type associated with the topic. Types are extensible and evolvable
• qos: is a collection of policies that express the non-functional properties of this topic, e.g. reliability, persistence, etc.
Topic
TopicTypeName
QoS
struct CarDynamics { @key string cid; long x; long y; float dx; long dy; }
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Vortex “knows” about application data types and uses this information provide type-safety and content-based routing
Content Awarenessstruct CarDynamics { @key string cid; long x; long y; float dx; long dy; }
cid x y dx dyGR 33N GO 167 240 45 0LO 00V IN 65 26 65 0AN 637 OS 32 853 0 50AB 123 CD 325 235 80 0
“dx > 50 OR dy > 50”
Type
CarDynamics
cid x y dx dyLO 00V IN 65 26 65 0AB 123 CD 325 235 80 0
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DDS provides a rich set of QoS-Policies to control local as well as end-to-end properties of data sharing
Some QoS-Policies are matched based on a Request vs. Offered (RxO) Model
QoS Policies
HISTORY
LIFESPAN
DURABILITY
DEADLINE
LATENCY BUDGET
TRANSPORT PRIO
TIME-BASED FILTER
RESOURCE LIMITS
USER DATA
TOPIC DATA
GROUP DATA
OWENERSHIP
OWN. STRENGTH
LIVELINESS
ENTITY FACTORY
DW LIFECYCLE
DR LIFECYCLE
PRESENTATION
RELIABILITY
PARTITION
DEST. ORDER
RxO QoS Local QoS
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DomainParticipant
DURABILITY
OWENERSHIP
DEADLINE
LATENCY BUDGET
LIVELINESS
RELIABILITY
DEST. ORDER
Publisher
DataWriter
PARTITION
DataReader
Subscriber
DomainParticipant
offered QoS
Topicwrites reads
Domain Idjoins joins
produces-in consumes-from
RxO QoS Policies
requested QoS
For data to flow from a DataWriter (DW) to one or many DataReader (DR) a few conditions have to apply:
The DR and DW domain participants have to be in the same domain
The partition expression of the DR’s Subscriber and the DW’s Publisher should match (in terms of regular expression match)
The QoS Policies offered by the DW should exceed or match those requested by the DR
Quality of Service
device-to-device communication
Latency Constraints
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Support for fine grained access control
Support for Symmetric and Asymmetric Authentication
Standard Authentication, Access Control, Crypto, and Logging plug-in API
Security
Arthur Dent
Arthur Dent
Ford Prerfect
Zaphod Beeblebrox
Marvin
Trillian
A(r,w), B(r)
A(r,w), B(r,w), X(r)
*(r,w)
*(r)
A(r,w), B(r,w), C(r,w)
Ford Prerfect
Zaphod Beeblebrox
Trillian
Marvin
A
B
A,BX
*
*
A,B,C
Identity Access RightsSessions are authenticated and communication is encrypted
Only the Topic included as part of the access rights are visible and accessible
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Boundary security support is enabled by Cloud-Link
Cloud-Link separates security concerns at different scales and also allows to control what information to expose
Boundary Security
Fog Computing Fog Computing
Fog Computing
Device-to-Cloud Communication
Peer-to-Peer (Brokerless)
Device-to-Device Communication
Cloud-LinkCloud-Link
TLS
TLS
Putting it all Together
Vortex device such are used to share data between different kinds of applications within a machine
Café can be used in Android based infotainment
Lite in ECU, sensors and onboard analytics
Vortex Fog is used to transparently (for in car apps) decouple and control the data sharing within and across the car
Vortex Fog also helps defining security boundaries and policies
Vortex Fog efficiently and securely deals with car to car communication
Vortex Fog efficiently and securely deals with cloud connectivity adapting traffic flows and protocols
Device-to-Cloud Communication
Cloud Analytics
Fog AnalyticsFog Analytics
Fog Analytics
Vortex Cloud efficiently and securely makes data available to any device at an Internet Scale
Device-to-Cloud Communication
Cloud Analytics
Fog AnalyticsFog Analytics
Fog Analytics
Vortex is the perfect data sharing platform for Connected and Autonomous Vehicle
In Summary
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