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Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
Interoperability for Intelligence Applications using Data-Centric Middleware
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Interoperability for Intelligence Applications using Data-Centric Middleware

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Presentation at the May 2012 Intelligence Workshop held in Rome Italy. …

Presentation at the May 2012 Intelligence Workshop held in Rome Italy.
Interoperability is key to reducing cost in the development and maintenance of applications that span multiple providers or must be supported over long periods of time. This presentation describes the role of network middleware technologies in such systems and how the use of a data-centric middleware, such as OMG DDS, makes developing such systems easier and more cost-effective.

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  1. Your systems. Working as one. Prerequisites of network centric intelligence:  Data Distribution BusIntelligence Workshop, Rome, May 2012Gerardo Pardo‐Castellote, Ph.D.   [gerardo@rti.com] CTO, Real‐Time Innovations, Inc.  [www.rti.com]Co‐author of DDS specification Co‐chair of the OMG Data‐Distribution SIG
  2. Enhance interoperability, reduce  system costs and increase  capability via data‐centric  system integrationDATA  ‐>  INFORMATION ‐> KNOWLEDGE + INTELLIGENCE © 2012 RTI • ALL RIGHTS RESERVED 2
  3. RTI: Global leader in DDS• Over 70% worldwide embedded messaging middleware market share• First with… – DDS API (2004) – RTPS interoperability protocol (2007)• Active in OMG standardization – Board of Directors member – Co‐chair DDS SIG – Chair DDS standard revision committees• Most mature solution – 15+ years of commercial availability – Diverse range of industries: defense, finance, medical, industrial control, power  generation, communications – 500+ commercial customers, 100+ research projects – 350,000+ licensed copies © 2012 RTI • ALL RIGHTS RESERVED 3
  4. Challenge:  More Data, More Speed, More SourcesTRENDS:• Growing Information Volume• Lowering Decision Latency• Increasing System Availability• Accelerating technology insertion  and deploymentNext‐generation systems needs:• Scalability• Robustness & Availability• Performance• Security• Integration & Evolution• Interoperability © 2012 RTI • ALL RIGHTS RESERVED 4 4
  5. The Key Challenge: Integration HighIntegration time & cost Low Small Large System Scale
  6. Interoperability• Operational – The ability of systems, units, or forces to provide  services to and accept services from other systems,  units, or forces, and to use the services so exchanged  to enable them to operate effectively together. (DoD Joint Publication 1‐02)• Software System – The ability of software systems to exchange  information without loss or change, and to use the  exchanged information to produce a useful result. 6 © 2012 RTI • ALL RIGHTS RESERVED
  7. Why Do We Care?• Interoperability is a force multiplier – System of Systems capability provide greatly increased effectiveness beyond the "sum of the parts" (individual  systems and technologies)• Operator’s perspective: – Interoperability allows use of costly systems at their full potential• Taxpayer perspective: – Interoperability allows us to pay once for a capability, vs.  many times, and opens the market for multiple  component providers. – Interoperability significantly reduces the largest portion of  total ownership cost ‐ operations and support. © 2012 RTI • ALL RIGHTS RESERVED
  8. State Of Practice• Recent studies have shown a growth in interoperability  policy issuance in DoD – Thousands of pages of directives, instructions, and  mandates – Numerous standards and architecture bodies in the DoD• Weak Correlation between Increased Interoperability  and Standards – Standards are necessary, but not sufficient for  interoperability• Conventional means of developing platform and  systems are complex, manpower intensive, and time  consuming. – Achieving Interoperability can increase complexity  © 2012 RTI • ALL RIGHTS RESERVED
  9. Approaches to Software Integration App Point‐to‐point App App App App App
  10. Approaches to Software Integration App Point‐to‐point App App App App App App Server/ App App Broker/ App ESB App App
  11. Approaches to Software Integration App Point‐to‐point App App App App App App Server/ App App Broker/ App ESB App App App App App App App App DDS  Data‐Centric Bus
  12. Levels of Conceptual Interoperability (LCIM) Level 6 Full assumptions and constraints of meaningful abstraction of  Conceptual Interoperability reality. Fully specified but independent model Level 5 Maintains state changes between systems during run time.  Dynamic Interoperability Includes assumptions and constraints that effect data interchange Level 4 Systems are aware of methods & procedures of other systems.  Pragmatic Interoperability Context is understood by all participating systems Level 3 Meaning of data is exchanged through use of a common  information model. The meaning of information is shared and  Semantic Interoperability unambiguously defined.Data‐CentricMiddleware Level 2 Common structure  or common data format for exchanging  information.  The  format of the information exchange is  Syntactic  Interoperability unambiguously defined Middleware Traditional Level 1 Communication protocol for exchanging data. Bits & Bytes are  Technical Interoperability exchanged in an unambiguous manner Level 0 Stand alone systems that have no interoperability No Interoperability
  13. Data‐Centric Middleware allows applications to be integrated to the Information Model APP APP APP APP Standard API Data Model Standard Mapping(*) DDS Global Data SpaceNo custom mappings / code necessaryDirect support for data‐centric actions: create, dispose, read/take Copyright © 2010 RTI ‐ All rights Reserved. . 13
  14. Everyday Example: Calendaring Alternative Process #1  (message‐centric): 1. Email: “Meeting Monday at 10:00.” 2. Email: “Here’s dial‐in info for meeting…” 3. Email: “Meeting moved to Tuesday” 4. You: “Where do I have to be? When?” 5. You: (sifting through email messages…) © 2012 RTI • ALL RIGHTS RESERVED 14
  15. Example: Calendaring Alternative Process #2: 1. Calendar: (add meeting Monday at 10:00) 2. Calendar: (add dial‐in info) 3. Calendar: (move meeting to Tuesday) 4. You: “Where do I have to be? When?” 5. You: (check calendar. Contains  consolidated‐state)The difference is state! The infrastructure consolidates changes and  maintains it © 2012 RTI • ALL RIGHTS RESERVED 15
  16. DDS:  Standards‐based Data‐Centric Integration Streaming Sensors Events Data Real‐Time Enterprise Actuators Applications Applications © 2012 RTI • ALL RIGHTS RESERVED 16
  17. Family of Specifications2008 2009 2010 2010 2012 2012UML Profile DDS for DDS  DDS‐STD‐C++ Web‐Enabled DDSfor DDS Lw CCM X‐Types DDS‐JAVA5 DDS Security App 2004 App App DDS Spec DDS 2006 DDS DDSImplementation DDS Implementation Implementation Interoperablity Network / TCP / UDP / IP © 2012 RTI • ALL RIGHTS RESERVED 17 17
  18. DDS mandated by key DoD Programs• UK Generic Vehicle Architecture – Mandates DDS for vehicle comm. – Mandates DDS‐RTPS for interop.• DISR – Mandates DDS for Pub‐Sub API – Mandates DDS‐RTPS for Interop• Army, OSD – UCS, Unmanned Vehicle Control • US Navy Open Architecture – Mandates DDS for Pub‐Sub• SPAWAR NESI – Mandates DDS for Pub‐Sub SOA © 2012 RTI • ALL RIGHTS RESERVED 18
  19. RTI Connext DDS Application Examples Aegis Weapon System ScanEagle UAV Lockheed Martin Boeing Radar, weapons, displays, C2 Sensors, ground station B‐1B Bomber Advanced Cockpit Ground Control  Boeing Station C2, communications, weapons Predator and SkyWarrior UAS General Atomics Telemetry data, multiple  workstations Common Link Integration  Processing (CLIP) Northrop Grumman Standards‐compliant interface  to legacy and new tactical  RoboScout data links Base10 Air Force, Navy, B‐1B and B‐52 Internal data bus and link to  communications center © 2012 RTI • ALL RIGHTS RESERVED 19
  20. RTI Connext DDS Application Examples Full‐immersion simulation Signal Processing National Highway  PLATH GMBH Transportation Safety  RTI supports modular  Authority programming across  Migrated from CORBA,  product line DCOM for performance Air‐Traffic Management INDRA. Large Telescopes Deployed in European Southern  UK, Germany, Spain Observatory Standards, Performance,  Performance &  Scalability Scalability 1000 mirrors, 1sec loop Radar Systems Industrial Control AWACS upgrade Schneider Electric Evolvability,  VxWorks‐based PLCs Mainteinability, and  supportability communicate via RTI‐DDS © 2012 RTI • ALL RIGHTS RESERVED 20
  21. RTI Connext DDS Application Examples Multi‐ship simulator Driver safety FORCE Technology Volkswagen Controls, simulation  vision systems, analysis, driver  display information systems Medical imaging Mobile asset tracking NMR and MRI Wi‐Tronix Sensors, RF generators, user  GPS, operational status  interface, control  over wireless links computers Automated trading Highway traffic  Automated Trading Desk (ATD,  monitoring now Citigroup) City of Tokyo Market data feed handlers,  Roadway sensors, roadside  pricing engines, algorithmic  kiosks, control center trading applications © 2012 RTI • ALL RIGHTS RESERVED 21
  22. Data‐Centric Qos‐Aware Pub‐Sub Model Virtual, decentralized global data space Source (key) Latitude Longitude Altitude UAV1 37.4 -122.0 500.0 UAV2 40.7 -74.0 250.0 UAV3 50.2 -0.7 2000.0 Persistence RecordingCRUD operations Service Service © 2012 RTI • ALL RIGHTS RESERVED 22
  23. Quality of Service (QoS)• Aside from the actual data to be delivered, users often  need to specify HOW to send it … … reliably (or “send and forget”) … how much data (all data , last 5 samples, every 2 secs) … how long before data is regarded as ‘stale’ and is discarded … how many publishers of the same data is allowed … how to ‘failover’ if an existing publisher stops sending data … how to detect “dead” applications ……• These options are controlled by formally‐defined  Quality of Service (QoS)
  24. Real‐Time Quality of Service (QoS) QoS Policy QoS Policy DURABILITY USER DATA User QoS HISTORY TOPIC DATAVolatility READER DATA LIFECYCLE GROUP DATA WRITER DATA LIFECYCLE PARTITION Presentation LIFESPAN PRESENTATION Infrastructure ENTITY FACTORY DESTINATION ORDER RESOURCE LIMITS OWNERSHIP Redundancy RELIABILITY OWNERSHIP STRENGTH Delivery TIME BASED FILTER LIVELINESS Transport DEADLINE LATENCY BUDGET CONTENT FILTERS TRANSPORT PRIORITY
  25. Operational robustness and  performance © 2012 RTI • ALL RIGHTS RESERVED 25
  26. Architecture for the next‐generation systems• Existing technologies are reaching robustness/performance/scalability limits• DDS provides a fundamentally new DataBus architecture and approach – Powerful data‐centric model – Ultra‐scalable and robust – Fully decentralized, peer‐to‐peer,  “no bottlenecks” architecture – Superior Wire Protocol – Standards‐based, multi‐platform Brokers as choke‐points Connext DDS Approach Single‐lane traffic No prioritization © 2012 RTI • ALL RIGHTS RESERVED 26
  27. Real‐Time Performance:U.S. Navy Analysis NESI part 5  v3.0 pg 70
  28. Performance Number of Subscribers • Reliable multicast • Fully meshed, reliable Orders of  magnitude faster than IT solutions Fastest DDS solution © 2012 RTI • ALL RIGHTS RESERVED 28
  29. Scalability • Scalable 600,000 Performance! • Millions of dataPer Subscriber (200 Bytes) 500,000 elements Messages per Second • .5m updates/sec 400,000 (batched) • 10s µs latency 300,000 • 1000s consumers per update 200,000 • Orders of magnitude  more scalable 100,000 than IT solutions 0                   200                   400                   600                   800                    0 1,000 Number of Subscribers 1  ~1000 subscribers, < 15% throughput decrease © 2012 RTI • ALL RIGHTS RESERVED 29
  30. Comparison with other technologies DDS/GSOAP/JMS/Notification Service Comparison - Latency 2500 2000 DDS JMS Notification Service 1500 1000 500 0 4 8 16 32 64 128 256 512 1024 2048 4096 8192 16384 Message Size (bytes) Message Length (samples) Adapted from Vanderbilt presentation at July 2006 OMG Workshop on RT Systems © 2012 RTI • ALL RIGHTS RESERVED 30
  31. Joint Battle Command (Blue Force Tracker):Poor Performance, Lack of MaintainabilityMission: Legacy Capability:• Track positions of friendly and  • 500K lines of code hostile forces on the battlefield • 8 yrs to develop• Design goal: 100K tracked  • 21 servers updates/sec • Achieved: 20K tracked updates/sec,  reliability and uptime challenges “This would not Next‐Gen Capability:have been possible • 50K lines of code—order of  magnitude less with any other • 1 yr to develop—8x lessknown technology.” • 1 laptop—20x less • Achieved: 250K+ tracked updates/sec,  —Network Ops Center Technical no single point of failure Lead © 2012 RTI • ALL RIGHTS RESERVED 31
  32. Conclusions• DDS is a mature international Standard from OMG – Platform Neutral: Operating systems and Programming  Languages – Deployed worldwide in Military systems and other  Demanding real‐time applications• DDS Is mandated by DoD for Publish‐Subscribe and  data‐distribution applications• DDS is an ideal integration platform for Intelligent  Systems – Highly Tunable via Quality of Service (QoS) – Rich services (persistence, filtering, high‐availability)• RTI is the Leading provider of DDS technology &  Services © 2012 RTI • ALL RIGHTS RESERVED 32
  33. Find out more… www.rti.com dds.omg.org community.rti.com www.omg.org demo.rti.com www.youtube.com/realtimeinnovations blogs.rti.com www.twitter.com/RealTimeInnov www.facebook.com/RTIsoftware www.slideshare.net/GerardoPardo © 2012 RTI • ALL RIGHTS RESERVED 33
  34. Thank You! © 2012 RTI • ALL RIGHTS RESERVED 34

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