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Building Autonomous and Connected Vehicle Systems with the Vortex Internet of Things Data Sharing Platform

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Although Autonomous and connected vehicles may sound somewhat futuristic applications of the Internet of Things (IoT), the reality is that these systems are being built and operated today in special environments. The design of these systems pose some unique challenges due to the constraints imposed by the criticality of the applications and the heterogeneity of the deployment environments. To put it another way, autonomous connected vehicles should not crash into each other, nor into other vehicles, whilst at the same time have to deal with connectivity that changes depending on their location, e.g. connectivity in down-town San Francisco may not be the same as the connectivity experience in the Joshua Tree National Park. This presentation will (1) showcase how PrismTech's Vortex Data Sharing Platform based on the Object Management Group's Data Distribution Service (DDS) standard is used today as the foundation of several autonomous and connected vehicles, (2) summarize the key requirements characteristic of these types of application, and (3) introduce the Vortex features that make it a perfect match for connectivity in autonomous and connected vehicle platforms and applications.

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Building Autonomous and Connected Vehicle Systems with the Vortex Internet of Things Data Sharing Platform

  1. 1. Building Autonomous and Connected Vehicle Systems with the Vortex IoT Data Sharing Platform Angelo  Corsaro,  PhD   Chief  Technology  Officer   angelo.corsaro@prismtech.com
  2. 2. HYPE CYCLE 2015 GARTNER
  3. 3. HYPE CYCLE 2015 GARTNER
  4. 4. HYPE CYCLE 2015 GARTNER
  5. 5. HYPE CYCLE 2015 GARTNER
  6. 6. What is IoT all About?
  7. 7. 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 —
  8. 8. the buzZ
  9. 9. CIoT Humanism digital
  10. 10. smart collar
  11. 11. connected f0rk
  12. 12. smart socks
  13. 13. Smart Lightbulbs
  14. 14. CIoT Platforms
  15. 15. CopyrightPrismTech,2015
  16. 16. CopyrightPrismTech,2015 Cloud-Centric Architecture Device-2-Cloud Communication
  17. 17. CopyrightPrismTech,2015
  18. 18. the Value IIoT
  19. 19. 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
  20. 20. How is IIoT Different?
  21. 21. device-to-device communication Latency Constraints
  22. 22. Autonomous Vehicles coordination of fast moving autonomous vehicles intermittent connectivity dynamic pairing of devices
  23. 23. CopyrightPrismTech,2014 Smart Factory 0.5 TB of data produced per day
  24. 24. Oil Rig 30000 data points only 1% of available data used today
  25. 25. CIoT / IIoT Differences
  26. 26. IIoT is concerned with reactive cyber-physical systems IIoT is about interacting with the physical world
  27. 27. Cloud-centric architectures centred around device-to-cloud communication are not applicable/sufficient for IIoT applications because of performance, connectivity and resource constraints
  28. 28. This essential difference introduces a series of requirements for IIoT platform that are not addressed by device-2-cloud centric IoT platforms
  29. 29. Connected Autonomous Vehicles l
  30. 30. Data Sharing needs
  31. 31. Device-2-Device communication Device-2-Cloud connectivity is not always possible due to connectivity challenges, response time or data volumes
  32. 32. Location Transparency Data should flow where needed transparently and independently from the location of its source
  33. 33. Vehicle diagnostics and sensor data should transparently flow where needed. For instance within the car for driving assistance and outside for preventive maintenance
  34. 34. Performance Transparency Data flows should be dynamically adapted to deal with QoS/ bandwidth differences across networks
  35. 35. The data that is sent across vehicles should be dynamically adjusted depending on the quality of the connection. Critical data should alleyways take priority!
  36. 36. Cloud + Fog Computing Cloud and Fog computing architectures should be transparently supported to allow for data to be processed wherever makes the most sense
  37. 37. Autonomous Vehicles coordination of fast moving autonomous vehicles intermittent connectivity dynamic pairing of devices
  38. 38. Durability Along with real-time data, historical data should be available for query and non-real-time analytics
  39. 39. Access to vehicle data must be secure!
  40. 40. Interoperability Data sharing standard are a pre- prerequisite for IoT. Without standards there is not interoperability, without interoperability there is not IoT
  41. 41. device-to-device communication Latency Constraints
  42. 42. Security Data-Level security should be provided to simplify the deployment of secure IoT systems
  43. 43. Access to vehicle data must be secure!
  44. 44. Vortex is a standard-based technology for efficient, ubiquitous, interoperable, secure, and platform independent data sharing across network connected devices in131 Characters
  45. 45. CopyrightPrismTech,2015 Proven in Defence / Aerospace Integrated Modular Vetronics Training & Simulation Systems Naval Combat Systems Air Traffic Control & Management Unmanned Air Vehicles Aerospace Applications
  46. 46. CopyrightPrismTech,2015 Broad Commercial Applications Agricultural Vehicle Systems Train Control Systems Complex Medical Devices Smart CitiesLarge Scale SCADA Systems High Frequency Auto-Trading
  47. 47. 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
  48. 48. CopyrightPrismTech,2015 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
  49. 49. Available across IT, Consumer and OT platforms Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog
  50. 50. Polyglot and Interoperable across Programming Languages Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog
  51. 51. 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
  52. 52. 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
  53. 53. 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
  54. 54. 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
  55. 55. Grasping the Idea
  56. 56. CopyrightPrismTech,2015 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 TopicA QoS TopicB QoS TopicC QoS TopicD QoS
  57. 57. Conceptual Model DDS Global Data Space ... Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS
  58. 58. Conceptual Model Actual Implementation Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS TopicD QoS TopicD QoS TopicA QoS DDS Global Data Space ... Data Writer Data Writer Data Writer Data Reader Data Reader Data Reader Data Reader Data Writer TopicA QoS TopicB QoS TopicC QoS TopicD QoS
  59. 59. 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 TopicA QoS TopicB QoS TopicC QoS TopicD QoS TopicD QoS TopicD QoS TopicA QoS The  communication  between   the  DataWriter  and  matching   DataReaders  can  be   “brokered”  but  still   exploiting  UDP/IP  (Unicast   and  Multicast)or  TCP/IP
  60. 60. CopyrightPrismTech,2015 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
  61. 61. Autonomous Vehicles coordination of fast moving autonomous vehicles intermittent connectivity dynamic pairing of devices
  62. 62. CopyrightPrismTech,2015 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 Topic Type Name QoS struct  CarDynamics  {        @key        string    cid;        long        x;      long    y;        float      dx;    long    dy;   }
  63. 63. CopyrightPrismTech,2015 Vortex “knows” about application data types and uses this information provide type- safety and content-based routing Content Awareness struct  CarDynamics  {        @key        string    cid;        long        x;      long    y;        float      dx;    long    dy;   } cid x y dx dy GR 33N GO 167 240 45 0 LO 00V IN 65 26 65 0 AN 637 OS 32 853 0 50 AB 123 CD 325 235 80 0 “dx  >  50  OR  dy  >  50” Type CarDynamics cid x y dx dy LO 00V IN 65 26 65 0 AB 123 CD 325 235 80 0
  64. 64. CopyrightPrismTech,2014 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
  65. 65. CopyrightPrismTech,2015 Domain Participant DURABILITY OWENERSHIP DEADLINE LATENCY BUDGET LIVELINESS RELIABILITY DEST. ORDER Publisher DataWriter PARTITION DataReader Subscriber Domain Participant offered QoS Topic writes reads Domain Id joins 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
  66. 66. device-to-device communication Latency Constraints
  67. 67. CopyrightPrismTech,2015 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,B X * * A,B,C Identity Access Rights Sessions are authenticated and communication is encrypted Only the Topic included as part of the access rights are visible and accessible
  68. 68. CopyrightPrismTech,2015 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
  69. 69. Putting it all Together
  70. 70. 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
  71. 71. 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
  72. 72. Vortex Fog efficiently and securely deals with car to car communication
  73. 73. Vortex Fog efficiently and securely deals with cloud connectivity adapting traffic flows and protocols Device-to-Cloud Communication Cloud Analytics Fog Analytics Fog Analytics Fog Analytics
  74. 74. Vortex Cloud efficiently and securely makes data available to any device at an Internet Scale Device-to-Cloud Communication Cloud Analytics Fog Analytics Fog Analytics Fog Analytics
  75. 75. Vortex is the perfect data sharing platform for Connected and Autonomous Vehicle In Summary
  76. 76. CopyrightPrismTech,2015

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