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DDS Over Low Bandwidth Data Links

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Presentation on DDS Over Low bandwidth Data Links by Jaime Martin Losa, CEO, eProsima - London Connext Conference 2014

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DDS Over Low Bandwidth Data Links

  1. 1. DDS over Low Bandwidth Data Links: Tactical Radios, Satellite, etc. Connext Conference - London October/08/2014 Jaime Martin Losa CEO eProsima JaimeMartin@eProsima.com +34 607 91 37 45 www.eProsima.com
  2. 2. eProsima in one shot  Experts on middleware, focused on DDS.  OMG Members. – RPC over DDS, Web Enabled DDS, DDS Security (Supporter)  Army Interoperability Standards Contributor – Spanish Army: Tactical Data Interface (IDT) – MIP: Adem Model  RTI Spanish Distributor .
  3. 3. Agenda  Initial Motivation, solution and results  DDS main concerns in Low Bandwidth Links  eProsima Low Bandwidth Plugins for DDS (Now RTI DIL Plugins) – Discovery Plugin – Compression Transport Plugin – RTPS Header Reduction Transport Plugin – Link Simulation Plugin  Some More hints - Questions  Appendix: – About eProsima – eProsima Success Cases  C2 Interoperability  Low Bandwidth Data Links
  4. 4. Initial Motivation, Solution and Results DDS in Low Bandwidth Enviroments
  5. 5. Initial Motivation  Bring DDS communications to the C2 Tactical level (Spanish Army): – Low Bandwidth Tactical Radios:  From 4800 bps shared – Frequent disconnections. – High packet loss rate.  Solution: Low Bandwidth Plugins for DDS – Simplified Discovery – Optimized RTPS headers – Compression
  6. 6. Results  DDS is mandated by the spanish Army for C2 interoperability in Tactical Radios, Satellite and Lan  Formal Interoperability Specification released, specifying how to use DDS and the information model (Spanish Tactical Data Interface, IDT)
  7. 7. Next Step: International C2 Interoperability: MIP ADEM  MIP: C2 International Interoperability (27 Countries) – Large and complex model  ADEM: Alternative Data Exchange Method (Simplified MIP Model) – Uses DDS for the Low Bandwidth profile
  8. 8. Real Performance Example: ADEM  ADEM MIP International Test (Jan 2014) – 2 C2 Nodes, Tactical Radios,  4800 bps SHARED = 600 bytes/sec – 12 Unit Positions/Second – Payload 44 bytes/position: 528 bytes/sec – Add RTPS & IP Headers: >100% of available bandwidth used:  Batching & Compression  Optimized RTPS headers  Simplified Discovery
  9. 9. Spanish Army Performance Test  Spanish Army Testing Example – VHF Radios – Bandwidth 4800 Bits/second SHARED – Number of nodes: 6  Example running 70 minutes: – 5 nodes: Each one sending its position and 3 more unit positions every 30s (5*4=20 positions in total/30 sec) – 1 node sending its position and 11 more (12 in total/30 sec) – 32 Positions/30 Sec (45 bytes/position) – Other traffic:  1 alarm every 180 sec  1 tactical message every 360 sec  2 obstacles (6 point area) every 1200 sec  2 Tactical line (6 point area) every 1200 sec  2 installations (6 point area) every 1200 sec
  10. 10. DDS main concerns in Low Bandwidth Links DDS in Low Bandwidth Enviroments
  11. 11. DDS main concerns in Low Bandwidth Links  Automatic Discovery is very chatty. – For N nodes the number of messages is proportional to N^2 – DDS is not going to work well Out of the box in bandwidths bellow 64kbits  DDS does not include data compression  The protocol (RTPS) headers are big for this kind of networks.  Fortunately, we can use the Low Bandwidth plugins for DDS to solve the problem
  12. 12. Low Bandwidth Discovery Plugin DDS in Low Bandwidth Enviroments
  13. 13. Overview  What is discovery?  Discovery phases – Participant discovery phase – Endpoint discovery phase  Low Bandwidth Discovery Plugin (LBDP)
  14. 14. What is discovery?  The process by which domain participants find out about each other’s entities – Each participant maintains database on other participants in the domain and their entities  Happens automatically behind the scenes – “anonymous publish-subscribe”  Dynamic discovery – Participants must refresh their presence in the domain or will be aged out of database – QoS changes are propagated to remote participants
  15. 15. Discovery phases  Two consecutive phases – Participant discovery phase  Participants discover each other  Best-effort communication, multicast (default) – Endpoint discovery phase  Participants exchange information about their datawriter and datareader entities  Reliable communication, unicast(default)  Steady state traffic to maintain liveliness of participants
  16. 16. Participant discovery phase  Participants periodically announce their presence using RTPS DATA message – Contains participant GUID, transport locators, QoS – Initially sent to all participants in “initial peers” list, then sent periodically to all discovered participants – Sent using best-effort Peer 1 (up) Peer 2 (up) Peer 3 (down) Hello! Hello! Hello! Initial peers: Peer 1 Peer 2 Peer 3
  17. 17. Endpoint discovery phase  Conversation between each pair.  DataWriter/DataReader discovery – Send out pub/sub DATA to every new participant – NACK for pub/sub info if not received from a known participant – Send out changes/additions/deletions to each participant  Uses reliable communication between participants  DDS matches up local and remote entities to establish communication paths
  18. 18. Discovery start-up traffic Node A Node B Participant created on A Send DATA to peer hosts Participant created on B Send DATA to peer hosts DATA participant A DATA participant B DATA participant A DATA participant B User creates Data Writer Foo Send DATA to participants in database DataWriter DATA Foo Add publication C to database of remote publications random sleep random sleep Add B to database of participants Add A to database of participants Already know about B (sent reliably)
  19. 19. Discovery Implementation  Discovery is implemented using DDS entities known as Built-in Data Writers and Built-in Data Readers – Uses same infrastructure as user defined Data Writers/Data Readers – Participant data is sent best effort & multicast – Publication/subscription data is sent reliably & unicast  Three Built-in topics (keyed): – DCPSParticipant – DCPSPublication – DCPSSubscription
  20. 20. Discovery Entities Participant 1 Participant Built-in Data Reader Publication Built-in Data Writer Subscription Built-in Data Reader Participant Built-in Data Writer Subscription Built-in Data Writer Publication Built-in Data Reader Participant Data Msg Publication Data Msg Subscription Data Msg Participant Built-in Data Reader Participant 2 Publication Built-in Data Writer Subscription Built-in Data Reader Participant Built-in Data Writer Subscription Built-in Data Writer Publication Built-in Data Reader Best Effort, Multicast Reliable, Unicast
  21. 21. LBDP  Goals: – Reduce the discovery information transmitted. – Reduce net traffic: Less Packets.  Scenario: – We now most details of the participant applications in advance.  Solution: – Suppress second discovery phase. – Mixed static and dynamic behavior. – Information about endpoints stored in XML files or Databases
  22. 22. LBDP: Discovery Entities Participant 1 Participant Built-in Data Reader Publication Built-in Data Writer Subscription Built-in Data Reader Participant Built-in Data Writer Subscription Built-in Data Writer Publication Built-in Data Reader Participant Built-in Data Reader Participant 2 Publication Built-in Data Writer Subscription Built-in Data Reader Participant Built-in Data Writer Subscription Built-in Data Writer Publication Built-in Data Reader Participant Data Msg Best Effort XML XML XML XML
  23. 23. Low Bandwidth Compression transport DDS in Low Bandwidth Enviroments
  24. 24. LBCT: Overview  Compression at Transport Level  Several compression libs used  Several modes of operation
  25. 25. LBCT: Compression at Transport Level  Compression at Transport Level – Stackable: Use it over any transport: UDP, Serial, Ad hoc…
  26. 26. LBCT:Several compression libs  Several compression libs can be used: – ZLIB – BZIP2 – LZO : LZO1X, LZO1B & LZO1F – UCL : UCL_NRV2B, UCL_NRV2D & UCL_NRV2E  Easy to add more by the user. – Through Public API.
  27. 27. Several modes of operation  Several modes of operation: – Fixed Algorithm – Algorithm depending on packet size. – Automatic: when CPU is not the bottleneck, the plugin select the best algorithm for each package.
  28. 28. Results  40% improvement in standard Discovery traffic – Applies also to Static Discovery  60-80% improvement in Data – We used several sample applications from command and control systems of Spanish Army.
  29. 29. Low Bandwidth RTPS Transport DDS in Low Bandwidth Enviroments
  30. 30. LB RTPS: Overview  Optimized RTPS for low bandwidth scenarios  Implemented as a transport.
  31. 31. LB RTPS: Optimized RTPS  RTPS Optimizations: – RTPS Header from 20 bytes to 1 byte. – RTPS SubmessageHeader from 4 to 1 byte. – RTPS extraflags for DATA and DATA_FRAG eliminated (1 byte) – ReaderID and WriterID from 4 to 1 byte each (so 2^3 writers or readers per participant) – SequenceNumber from 8 to 5 or less bytes (more than enough for these scenarios)  Save more than 30 bytes!
  32. 32. LB RTPS: Implemented as a transport  Implemented as a transport  Stackable: – Can be used with any transport and it is stackable, so for example you could use: – LB RTPS -> UDP – LB RTPS -> Compression Transport -> UDP
  33. 33. Low Bandwidth Simulation Transport DDS in Low Bandwidth Enviroments
  34. 34. LB Simulation Transport: Overview  Simulate your low bandwidth scenario  Implemented as a Transport plugin (stackable)  Two operation modes: – Simple Channel mode: Easy to Set Up  The bandwidth is controlled for each node independently – Advanced Channel mode:  Bandwidth controlled accounting the activity in all the nodes.
  35. 35. LB Simulation Transport: Simulate your low bandwidth scenario  Simulate your low bandwidth scenario: – Designed to cover a variety of devices:  Tactical Radios  Satellite links – General purpose.
  36. 36. Low Bandwidth: Hints DDS in Low Bandwidth Enviroments
  37. 37. Low Bandwidth Scenarios: Hints  Use Best Effort or NACK Based Reliability  Use Multicast in Radio Scenarios  Flow controllers  Optimize Types. – Sparse Types.  Call us 
  38. 38. Low Bandwidth Scenarios: Hints (II)  eProsima Smart Flow Controller for DDS – Take into account the network state in real time  The product calculates the available bandwidth in real time with the latencies & packet loss – Assign real priorities and bandwidth resources to your DDS Topics  In Terms of the available bandwidth.
  39. 39. Want to know more?  www.eProsima.com  Youtube: https://www.youtube.com/user/eprosima  Mail: JaimeMartin@eProsima.com  Phone: +34 607913745  Twitter: @jaimemartinlosa  http://es.slideshare.net/JaimeMartin-eProsima
  40. 40. Appendixes
  41. 41. About eProsima
  42. 42. About eProsima  Experts on middleware, focused on DDS.  OMG Members.  Army Interoperability Standards – Spanish Army: Tactical Data Interface (IDT) – MIP: Adem Model .
  43. 43. About eProsima: Products And Services  eProsima Products: – DDS based: Plugins, add-ons, adaptors, etc  Services: – Communication modules, App development, DDS training, Support.  R&D: – R&D Projects with enterprises and universities.  Quality: ISO 9001 – Design, Development, Marketing and Support of Software.
  44. 44. Customers (I)  Amper Programas: – BMS – Simacet (Main Spanish C2 System)  Cassidian: – UAVs - Neuron, Atlante  Ground Station Comm Server – Comfut  INDRA: – Defense (BMS, UAV PASI) – Air Traffic Control, – SESAR, ATC Interoperability – Energy (InSpeed)  Spanish Army:, – IDT :Tactical Data Interface
  45. 45. Customers (II)  Isdefe  Spanish Army: JCISAT, DGAM  CATEC-FADA: R&D Aerospatial  Santa Barbara: Armoured Vehicles  RTI  GMV
  46. 46. Customers (III)  Tecnobit: COSMOS, Reserved Projects.  IKERLAN: R&D.  Navantia: F105 (Aegis)  Boeing: Atlantida, Swim suit
  47. 47. eProsima Products.- Index  eProsima Smart Flow Controller for DDS. – Flow control for Low Bandwidth  eProsima RPC over DDS: – Remote procedure calls framework over DDS.  eProsima Fast Buffers – Fast Serialization engine.  eProsima Dynamic Fast Buffers. – Fast Serialization engine. No IDL Required, serialization support is generated at runtime.  eProsima DDS Non-Intrusive Recorder. – Stores DDS communication history in a data base.
  48. 48. Ongoing Project  FP7: KIARA, Future Internet Middleware – FI-WARE 1st open call – Based on eProsima RPC over DDS & OMG DDS – Lots of new features:  Improved IDL  Direct Use of Application native types  New formats of marshalling (SOAP, RestFul)  Web Services compatibility  Protocol negotiation  Extended transport support  High performance dispatching agent (RPC)
  49. 49. eProsima Success Cases
  50. 50. RTI DDS DIL Plugins: Disconnected and Intermitent Links  eProsima developed the plugins for the Spanish Army Tactical Radios, and later were adquired by RTI.  Allow the use of DDS in very low bandwidth links, such as Tactical Radios and Satellite. – Tested from 2400 bps
  51. 51. Tactical Data Interface: Spanish Army  C2 Interoperability Comm layer: – Tactical Radios  From 2400bps – Satellite  Mandated for all the Spanish Army C2 systems. – Already implemented in the their main C2 systems eProsima developed the army C2 comm layer using RTI Connext DDS optimized for low bandwidth enviroments. The project included the design of the Data Model and QoS requisites for the Army.
  52. 52. C2 Systems: INDRA & Amper  eProsima Provides a DDS based comm layer for INDRA and Amper C2 Systems. eProsima implemented the mandated Spanish Army Tactical Data Interface for Simacet (Main Spanish Army C2 System, Amper) and BMS (Tanks C2 System, INDRA & Amper)
  53. 53. Tactical Messaging Bridge  Unified mail and chat: Internet, NATO and Tactical for the Spanish Army.  Enable Complete Messaging on the tactical radio network.
  54. 54. SESAR - INDRA ATC  eProsima provides middleware research and prototyping for ATC Interoperability  Among the different middleware technologies studied, DDS and WS are the SESAR proposed technologies for ATC interoperability.
  55. 55. Cassidian: nEURon and Atlante GS  eProsima provides the comm layer for the ground station comm server. eProsima Non-Intrusive Recorder is used to record the communications for later analisys.
  56. 56. FI-WARE Middleware  eProsima has been selected to develop Future Internet Middleware in the FI-WARE programme.  DDS will be the core technology Fi-WARE is a consortium of over more than 30 companies and universities including Telefonica, Siemens, SAP, Atos… eProsima will partner in this project with the German Universities DKFI and CISPA and the Swiss ZHAW.
  57. 57. Remote Application Client / Server, Publisher / Subscriber Application Declarative Data/Function descritption API / Data Access Data / Function Mapping Compile time or Embedded Runtime Compiler/Interpreter Marshalling Transport Mechanis ms Wire- Protocols RPC Pub/Sub Transport Protocols TCP UDP TLS, DTLS Shared Memory Backplane/ Fabric XML JSON CDR SDN Plugin Data Transfer Security / QoS Parameter Security / QoS Policy Function Stub Function Skleleton QoS Data Writer Data Reader - DDS / RTPS REST / HTTP Negotiation Publisher Subscriber RPC Server RPC Client Prepare Initialize IDL Parser • IDL based on OMG IDL • WADL Security Dispatching I2ND GE FI-WARE Middleware: DDS Based
  58. 58. Thank you! Jaime Martin Losa CEO eProsima JaimeMartin@eProsima.com +34 607 91 37 45 www.eProsima.com

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