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

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Information about Building Autonomous and Connected Vehicle Systems with the Vortex...

Published on September 25, 2015

Author: PrismTech1

Source: slideshare.net

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. HYPE CYCLE 2015 GARTNER

3. HYPE CYCLE 2015 GARTNER

4. HYPE CYCLE 2015 GARTNER

5. HYPE CYCLE 2015 GARTNER

6. What is IoT all About?

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. the buzZ

9. CIoT Humanism digital

10. smart collar

11. connected f0rk

12. smart socks

13. Smart Lightbulbs

14. CIoT Platforms

15. CopyrightPrismTech,2015

16. CopyrightPrismTech,2015 Cloud-Centric Architecture Device-2-Cloud Communication

17. CopyrightPrismTech,2015

18. the Value IIoT

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. How is IIoT Different?

21. device-to-device communication Latency Constraints

22. Autonomous Vehicles coordination of fast moving autonomous vehicles intermittent connectivity dynamic pairing of devices

23. CopyrightPrismTech,2014 Smart Factory 0.5 TB of data produced per day

24. Oil Rig 30000 data points only 1% of available data used today

25. CIoT / IIoT Differences

26. IIoT is concerned with reactive cyber-physical systems IIoT is about interacting with the physical world

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. This essential difference introduces a series of requirements for IIoT platform that are not addressed by device-2-cloud centric IoT platforms

29. Connected Autonomous Vehicles l

30. Data Sharing needs

31. Device-2-Device communication Device-2-Cloud connectivity is not always possible due to connectivity challenges, response time or data volumes

32. Location Transparency Data should flow where needed transparently and independently from the location of its source

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. Performance Transparency Data flows should be dynamically adapted to deal with QoS/ bandwidth differences across networks

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. 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. Autonomous Vehicles coordination of fast moving autonomous vehicles intermittent connectivity dynamic pairing of devices

38. Durability Along with real-time data, historical data should be available for query and non-real-time analytics

39. Access to vehicle data must be secure!

40. Interoperability Data sharing standard are a pre- prerequisite for IoT. Without standards there is not interoperability, without interoperability there is not IoT

41. device-to-device communication Latency Constraints

42. Security Data-Level security should be provided to simplify the deployment of secure IoT systems

43. Access to vehicle data must be secure!

44. Vortex is a standard-based technology for efficient, ubiquitous, interoperable, secure, and platform independent data sharing across network connected devices in131 Characters

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. CopyrightPrismTech,2015 Broad Commercial Applications Agricultural Vehicle Systems Train Control Systems Complex Medical Devices Smart CitiesLarge Scale SCADA Systems High Frequency Auto-Trading

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. 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. 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. Polyglot and Interoperable across Programming Languages Device-2-DeviceDevice-2-Cloud Fog-2-Cloud Device-2-Fog Cloud-2-Cloud Fog-2-Fog

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. 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. 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. 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. Grasping the Idea

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. 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. 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. 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. 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. Autonomous Vehicles coordination of fast moving autonomous vehicles intermittent connectivity dynamic pairing of devices

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. 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. 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. 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. device-to-device communication Latency Constraints

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. 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. Putting it all Together

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. 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. Vortex Fog efficiently and securely deals with car to car communication

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. 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. Vortex is the perfect data sharing platform for Connected and Autonomous Vehicle In Summary

76. CopyrightPrismTech,2015

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