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Data-Distribution
Service (DDS)
The Ideal Bus for CEP
     dds/2008-03-04
     Gerardo Pardo-Castellote, Ph.D.
     Co-Chair Data-Distribution SIG
     CTO, Real-Time Innovations, Inc.
     13 March 2008
Agenda


     Introduction

     Middleware and CEP

     The OMG DDS standard as a message bus for CEP

     Conclusion




2                   © 2007 Real-Time Innovations, Inc.
History:              DDS the Standard
     Data Distribution Service for Real-Time Systems
      – Adopted in June 2003
      – Finalized in June 2004
      – Revised June 2005, June 2006
      – Joint submission (RTI, THALES, OIS)
      – Specification of API for Data-Centric Publish-Subscribe in real-
        time distributed systems.

     Interoperability wire protocol
      – Adopted in July 2006
      – Revised in July 2007

     Multiple Implementations
      – 4 commercial
      – 3 open source
      – Several more in-house
3                          © 2007 Real-Time Innovations, Inc.
DDS Adoption – Aerospace & Defense

              Boeing
              AWAKS          Northtrop
                                  E2C
                               Hawkeye



             Boeing
             Future Combat
             Systems
                              Raytheon
                                 SSDS


             Lockheed
             AEGIS                 Insitu
                             Unmanned
                             Air Vehicles

4
DDS Adoption – Transportation, Industrial


               WiTronix
               Train and vehicle         Schneider Electric
               Tracking               Industrial Automation



                Tokyo Japan
                Traffic Control                   Kuka
                                               Robotics




                EU and US
                Air Traffic
                Management                     Varian
                                   Medical Instruments
5
Many others




6                 © 2007 Real-Time Innovations, Inc.
DDS Mandates for Net-Centric Systems

     DISR (formerly JTA)
      – DoD Information Technology
         Standards Registry

     US Navy Open Architecture

     FCS SOSCOE
      – Future Combat System –
         System of System Common
         Operating Environment

     NESI
      – Net-centric Enterprise Solutions
         for Interoperability

     UK MOD & NATO
      – Advocating Open Systems

7                               © 2007 Real-Time Innovations, Inc.
Middleware and CEP: The hose that feeds the engine




        Inputs                                             Outputs


                      CEP Engine




                     CEP Engine




8                     © 2007 Real-Time Innovations, Inc.
Middleware and CEP: Scalability & Load Balancing




                     CEP Engine




                      CEP Engine




      CEP Engine                                           CEP Engine
9                     © 2007 Real-Time Innovations, Inc.
Middleware and CEP: Integration &
     Interoperability



                    Vendor 2




                      Vendor 3




        Vendor 1                                          Vendor 4
10                   © 2007 Real-Time Innovations, Inc.
Implementing the Global Event Bus/Data
     Streams




                                EventType1

                                    EventType2

                          Global Event Bus
                              EventType2



                 ADAPTOR != MIDDLEWARE
     Multiple adaptor technologies will be needed… but not all are created equal
     It is highly desirable to use a middleware where the event model and use-
     case requirements are handled as first-class citizens
     Event semantic model can be pushed into the middleware information
11   model                         © 2007 Real-Time Innovations, Inc.
Standardizing the Adaptor/Transport


     NEEDED:
       Not so much a standard adaptor…

       …but:
        – A standard event meta-model
               Relevant OMG standards: UML, MOF, OCL, …
        – A ‘standard’ way to adapt to the existing Transports/Message
          Busses & information model
               Using the same Adaptor technology will not allow CEP engines to
               “interoperate”
               Relevant OMG standards: DDS, CORBA Notification Service


            Communicate != Interoperate

12                              © 2007 Real-Time Innovations, Inc.
Requirements on a CEP Message Bus

     Fit to the CEP information Model
      – CEP engines need access to data regardless of its source
      – CEP operates on structured data, not opaque messages

     Performance & Scalability
      – CEP systems are event-driven
      – CEP operates on streaming data and has low-latency & high-
        throughput requirements


     Configurability, QoS, Filtering & Services
      – CEP is deployed in critical systems that be robust to failures
      – CEP weaves streams with different QoS requirements (updates
        rates, priority)
      – CEP often needs access to only a subset of the information
13                          © 2007 Real-Time Innovations, Inc.
DDS: The best “message bus” for CEP?

     Fit to the CEP information Model
      – DDS is Data-Centric, not message centric
      – Beyond messaging DDS also does “state management”
      – DDS Supports Topic-Based and Content-Based Subscriptions
      – DDS built-in Window/Time selectors delivers *only* relevant data

     Performance & Scalability
      – DDS offers notification-based APIs
      – DDS has the best performance (latency, throughput, jitter, scalability) of
         any standard middleware technology

     Configurability, QoS, Filtering & Services
      – DDS Publish-Subscribe model delivers wherever needed
      – DDS has rich QoS to support real-time event-driven systems (latency
        budget, priority, etc.)
      – DDS Built-in Fault-Tolerance Mechanism allow for redundant sources of
        data
      – DDS built-in services Persistence and Historical Data Services ensures
        relevant data is never lost
14                               © 2007 Real-Time Innovations, Inc.
#1 DDS Data-Centric Model

     “Global Data Space” generalizes Subject-Based Addressing
       – Data objects addressed by DomainId, Topic and Key
       – Domains provide a level of isolation
       – Topic groups homogeneous subjects (same data-type & meaning)
       – Key is a generalization of subject
                 Key can be any set of fields, not limited to a “x.y.z …” formatted string
       – Data Structure is known by the middleware


                                                                               Data Reader
       Data Writer            Topic


                                                                                       Data Reader
         Data Writer



                                                                                Data Reader
         Data Writer


15                                      © 2007 Real-Time Innovations, Inc.
#1 DDS Data-Centric Model

     “Global Data Space” generalizes Subject-Based Addressing
       – Data objects addressed by DomainId, Topic and Key
       – Domains provide a level of isolation
       – Topic groups homogeneous subjects (same data-type & meaning)
       – Key is a generalization of subject
                 Key can be any set of fields, not limited to a “x.y.z …” formatted string
       – Data Structure is known by the middleware


                                                                               Data Reader
       Data Writer              Key (subject)



                                                                                       Data Reader
         Data Writer



                                                                                Data Reader
         Data Writer


16                                      © 2007 Real-Time Innovations, Inc.
#1 DDS Data-Centric Model

     “Global Data Space” generalizes Subject-Based Addressing
       – Data objects addressed by DomainId, Topic and Key
       – Domains provide a level of isolation
       – Topic groups homogeneous subjects (same data-type & meaning)
       – Key is a generalization of subject
                 Key can be any set of fields, not limited to a “x.y.z …” formatted string
       – Data Structure is known by the middleware


                                                                               Data Reader
       Data Writer

                            Data Object
                                                                                       Data Reader
         Data Writer



                                                                                Data Reader
         Data Writer


17                                        © 2007 Real-Time Innovations, Inc.
Subscriptions: By Topic, Subject, Content

      Topic: “Market Data”
                              Key Fields                                Other Fields
                                                                                 Payload
      Field    Source         Symbol      Type     Exchange       Volume       Bid     Ask         …

      Value          *             *        *         *                               *


     Topic: “Order Entry”
                            Key Fields                                Other Fields

     Field    Symbol         Type      Exchange   OrderNumber OrderKind       Stop        Limit           …

     Value      *              *        NYSE                                      *


                    Subject Filter (for a Reader)

      Topic: “Market Data”
                      Key Fields                                       Other Fields
     Field    Source         Symbol      Type     Exchange                     Payload


     Value REUTERS             *          EQ       NYSE                  Volume > x, Ask < y


18                                                 © 2007                 Payload Filter (for a Reader)
                         Subject Filter (for a Reader) Real-Time Innovations, Inc.
DDS communications model

                         Data         Domain                                            Data         Domain
        New              Writer     Participant                                        Reader      Participant
                        “Alarm”
                                                                Got new                “Alarm”
     subscriber!                                                 data
                                  Offered                                                        Offered
             Listener             QoS                                       Listener             QoS




          Participants scope the global data space (domain)
          Topics define the data-objects (collections of subjects)
          Writers publish data on Topics
          Readers subscribe to data on Topics
          QoS Policies are used configure the system
          Listeners are used to notify the application of events
19                                     © 2007 Real-Time Innovations, Inc.
Demo: Concepts                                                         Start demo

      Display Area:
      Shows state of objects                                       Topics
                                                                   – Square, Circle, Triangle
                                                                   – Attributes
                                                                   Data types (schemas)
                                                                   – Shape (color, x, y, size)
                                                                            Color is instance Key
                                                                   – Attributes
                                                                            Shape & color used for key
                                                                   QoS
                                                                   –   Deadline, Liveliness
                                                                   –   Reliability, Durability
                                                                   –   History, Partition
     Control Area:                                                 –   Ownership
20
     Allows selection of objects and Real-Time Innovations, Inc.
                                  © 2007
                                         QoS
QoS: Quality of Service

     Standardized Middleware QoS semantics

       QoS Policy                                QoS Policy
       DURABILITY                                USER DATA
       HISTORY (per subject)                     TOPIC DATA
       READER DATA LIFECYCLE                     GROUP DATA
       WRITER DATA LIFECYCLE                     PARTITION
       LIFESPAN                                  PRESENTATION
       ENTITY FACTORY                            DESTINATION ORDER
       RESOURCE LIMITS                           OWNERSHIP
       RELIABILITY                               OWNERSHIP STRENGTH
       TIME BASED FILTER                         LIVELINESS
       DEADLINE                                  LATENCY BUDGET
       CONTENT FILTERS                           TRANSPORT PRIORITY
21                             © 2007 Real-Time Innovations, Inc.
Demo: Quality of Service (QoS)
                                                                                        Start demo

     Writers and readers state
     Their needs
                                                                      Topics
                                                                      – Square, Circle, Triangle
                                                                      – Attributes
                                                                      Data types (schemas)
                                                                      – Shape (color, x, y, size)
                                                                               Color is instance Key
                                                                      – Attributes
                                                                               Shape & color used for key
                                                                      QoS
                                                                      –   Deadline, Liveliness
                                                                      –   Reliability, Durability
                                                                      –   History, Partition
                                                                      –   Ownership
     RTI DDS delivers
22                               © 2007 Real-Time Innovations, Inc.
DDS: The best “message bus” for CEP?

     #1 Fit to the CEP information Model
      – DDS is Data-Centric, not message centric
      – DDS Supports Topic-Based and Content-Based Subscriptions
      – DDS built-in Window/Time selectors delivers *only* relevant data

     #2 Performance & Scalability
      – DDS offers notification-based APIs
      – DDS has the best performance (latency, throughput, jitter, scalability) of
         any standard middleware technology

     #3 Configurability, QoS, Filtering & Services
      – DDS Publish-Subscribe model delivers wherever needed
      – DDS has rich QoS to support real-time event-driven systems (latency
        budget, priority, etc.)
      – DDS Fault-Tolerance Mechanism allows for redundant sources of data
      – DDS built-in services Persistence and Historical Data Services ensures
        relevant data is never lost
23                               © 2007 Real-Time Innovations, Inc.
Data-Distribution and Real-Time
      Messaging Technologies and Standards




                                                        Web Services




                                                             Java              RTSJ (soft RT)                     RTSJ (hard RT)




                                                             Java/RMI
                                                             Java/JMS



                                                             CORBA                                 RT CORBA



                                                                              Data Distribution Service / DDS



                                                                                                                             MPI


                                             Non-real-time              Soft real-time                  Hard real-time             Extreme real-time
24                                                                                © 2007 Real-Time Innovations, Inc.
     Adapted from NSWC-DD OA Documentation
Latency – (Linear Scale)
     IBM HS20 blades
     Dual 2.8 GHz Xeon, 1 GB RAM
     Gigabit Ethernet

                  DDS/JMS/Notification Service Comparison - Latency
      2500




      2000


                  DDS         JMS      Notification Service
      1500




      1000




      500




        0
             16    32    64    128   256         512       1024      2048       4096   8192   16384   32768   65536
                                               Message Size (bytes)

        Adapted from Vanderbilt presentation at July 2006 OMG Workshop on RT Systems
25                                         © 2007 Real-Time Innovations, Inc.
Jitter – (Linear Scale)

                                                                                            DDS/CORBA Notification Service Comparison - Jitter

                                                                      100
                                                                       DDS/JMS/CORBA Notification Service Comparison - Jitter
                                         Standard Deviation (usecs)




                                                                       80
                                  2000

                                  1800
                                                                                            DDS       JMS             Notification service
                                                                       60
     Standard Deviation (usecs)




                                  1600

                                  1400
                                                                       40        DDS          JMS          Notification service
                                  1200

                                  1000
                                                                       20
                                   800

                                   600
                                                                        0
                                   400
                                                                             16        32      64    128       256        512       1024         2048    4096     8192     16384     32768   65536
                                   200                                                                                  Message Size (bytes)
                                     0
                                                          16                32     64        128    256      512      1024       2048       4096        8192    16384    32768     65536
                                                                                                           Message Size (bytes)



                                         Source: Vanderbilt presentation at July 2006 OMG Workshop on RT Systems
26                                                                                                          © 2007 Real-Time Innovations, Inc.
DDS : Low Latency and Jitter
                                         Latency and Jitter on Unloaded Network
                              400
     Latency (microseconds)




                              350
                              300
                                                                                                   Maximum
                              250
                                                                                                   99.99%
                              200                                                                  99%
                              150                                                                  Median
                                                                                                   Minimum
                              100
                              50
                               0
                                    32   64   128 256 512 1024 2048 4096 8192
                                                  Message/Data Size (bytes)
        Reliable, ordered delivery over
        Gigabit Ethernet between 2.0 GHz Opteron processors
        running 32-bit Red Hat Enterprise Linux 4.0
27                                                            © 2007 Real-Time Innovations, Inc.
DDS: Low Overhead Enables High
                          Throughput
                          70,000                                                                                      1000

                                                                                                                      900
                          60,000
                                                                                                                      800

                          50,000                                                                                      700




                                                                                                                             Megabits per Second
     Updates per Second




                                                                                                                      600
                          40,000
                                                                                                                      500
                          30,000
                                                                                                                      400

                          20,000                                                                                      300

                                                                                                                      200
                          10,000
                                                                                                                      100

                              0                                                                                       0
                                   16   32   64    128        256        512        1024 2048 4096 8192 16384 32768
                                                                             Message/Data Size
     Reliable, ordered delivery over
     Gigabit Ethernet between 2.0 GHz Opteron
     processors running 32-bit Red Hat Enterprise Linux 4.0
28                                                            © 2007 Real-Time Innovations, Inc.
DDS: Scalable Performance (Confirmed
                                          Reliability)
                                         60,000



                                         50,000
     Point-to-Point Updates per Second




                                         40,000                                                               1-1
                                                                                                              1-10
                                                                                                              1-24
                                         30,000



                                         20,000



                                         10,000



                                             0
                                                  16   32              64                   128       256   512      1024
                                                            Message/Data Size (bytes - without batching)
         Reliable, ordered delivery over
         Gigabit Ethernet between 2.0 GHz Opteron processors
29       running 32-bit Red Hat Enterprise Linux 4.0             © 2007 Real-Time Innovations, Inc.
DDS operates without brokers

             DDS                                                 Broker-based
                                                                 Middleware




     No Brokers =>     Better Performance & Determinism
                     + Increased Robustness
30                          © 2007 Real-Time Innovations, Inc.
DDS: The best “message bus” for CEP?

     #1 Fit to the CEP information Model
      – DDS is Data-Centric, not message centric
      – DDS Supports Topic-Based and Content-Based Subscriptions
      – DDS built-in Window/Time selectors delivers *only* relevant data

     #2 Performance & Scalability
      – DDS offers notification-based APIs
      – DDS has the best performance (latency, throughput, jitter, scalability) of
         any standard middleware technology

     #3 Configurability, QoS, Filtering & Services
      – DDS Publish-Subscribe model delivers wherever needed
      – DDS has rich QoS to support real-time event-driven systems (latency
        budget, priority, etc.)
      – DDS Fault-Tolerance Mechanism allows for redundant sources of data
      – DDS built-in services Persistence and Historical Data Services ensures
        relevant data is never lost
31                               © 2007 Real-Time Innovations, Inc.
#3 QoS and Powerful Services

       – Redundancy &                 QoS Policy              QoS Policy
         Failover                     DURABILITY              USER DATA
       – Persistent Data              HISTORY (per subject)   TOPIC DATA

       – Last value cache             READER DATA             GROUP DATA
                                      LIFECYCLE
       – Historical cache             WRITER DATA             PARTITION
                                      LIFECYCLE
                                      LIFESPAN                PRESENTATION

                                      ENTITY FACTORY          DESTINATION ORDER

                                      RESOURCE LIMITS         OWNERSHIP

                                      RELIABILITY             OWNERSHIP STRENGTH

                                      TIME BASED FILTER       LIVELINESS

                                      DEADLINE                LATENCY BUDGET

                                      CONTENT FILTERS         TRANSPORT PRIORITY


32                      © 2007 Real-Time Innovations, Inc.
Ownership and High Availability

     Producer / Writer
                               I1 Prim
       strength=10                    ary
                                                                     Topic T1
     Producer / Writer         I1 Backup
        strength=5
                                                      I2 Primary     I1   I2
     Producer / Writer         I2 Backup
        strength=1

          Owner determined per subject
          Only extant writer with highest strength can publish a subject (or
          topic for non-keyed topics)
          Automatic failover when highest strength writer:
           – Loses liveliness
           – Misses a deadline
           – Stops writing the subject

          Shared Ownership allows any writer to update the subject
33                              © 2007 Real-Time Innovations, Inc.
Data Persistence
     A standalone service that persists data outside of
     the context of a DataWriter
                                                               Data
                                Data                           Writer            Data
                                Writer                                          Reader




                      Data                               Global
                     Reader                            Data Space




                                  Persistence                       Persistence
                                    Service                           Service

                                   Permanent                            Permanent
                                    Storage                              Storage



34                        © 2007 Real-Time Innovations, Inc.
Conclusion

       To get the best performance from your CEP you
       need the best message bus

       DDS is a natural fit for CEP:
       – The Data-Centric Pub-Sub information model is an
         excellent match to the CEP structured event model
       – DDS supports many of the CEP use-cases and QoS
         as first-class citizens
       – DDS offers the best performance and latency of any
         middleware standard


35                     © 2007 Real-Time Innovations, Inc.

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Dds the ideal_bus_for_event_processing_engines

  • 1. Data-Distribution Service (DDS) The Ideal Bus for CEP dds/2008-03-04 Gerardo Pardo-Castellote, Ph.D. Co-Chair Data-Distribution SIG CTO, Real-Time Innovations, Inc. 13 March 2008
  • 2. Agenda Introduction Middleware and CEP The OMG DDS standard as a message bus for CEP Conclusion 2 © 2007 Real-Time Innovations, Inc.
  • 3. History: DDS the Standard Data Distribution Service for Real-Time Systems – Adopted in June 2003 – Finalized in June 2004 – Revised June 2005, June 2006 – Joint submission (RTI, THALES, OIS) – Specification of API for Data-Centric Publish-Subscribe in real- time distributed systems. Interoperability wire protocol – Adopted in July 2006 – Revised in July 2007 Multiple Implementations – 4 commercial – 3 open source – Several more in-house 3 © 2007 Real-Time Innovations, Inc.
  • 4. DDS Adoption – Aerospace & Defense Boeing AWAKS Northtrop E2C Hawkeye Boeing Future Combat Systems Raytheon SSDS Lockheed AEGIS Insitu Unmanned Air Vehicles 4
  • 5. DDS Adoption – Transportation, Industrial WiTronix Train and vehicle Schneider Electric Tracking Industrial Automation Tokyo Japan Traffic Control Kuka Robotics EU and US Air Traffic Management Varian Medical Instruments 5
  • 6. Many others 6 © 2007 Real-Time Innovations, Inc.
  • 7. DDS Mandates for Net-Centric Systems DISR (formerly JTA) – DoD Information Technology Standards Registry US Navy Open Architecture FCS SOSCOE – Future Combat System – System of System Common Operating Environment NESI – Net-centric Enterprise Solutions for Interoperability UK MOD & NATO – Advocating Open Systems 7 © 2007 Real-Time Innovations, Inc.
  • 8. Middleware and CEP: The hose that feeds the engine Inputs Outputs CEP Engine CEP Engine 8 © 2007 Real-Time Innovations, Inc.
  • 9. Middleware and CEP: Scalability & Load Balancing CEP Engine CEP Engine CEP Engine CEP Engine 9 © 2007 Real-Time Innovations, Inc.
  • 10. Middleware and CEP: Integration & Interoperability Vendor 2 Vendor 3 Vendor 1 Vendor 4 10 © 2007 Real-Time Innovations, Inc.
  • 11. Implementing the Global Event Bus/Data Streams EventType1 EventType2 Global Event Bus EventType2 ADAPTOR != MIDDLEWARE Multiple adaptor technologies will be needed… but not all are created equal It is highly desirable to use a middleware where the event model and use- case requirements are handled as first-class citizens Event semantic model can be pushed into the middleware information 11 model © 2007 Real-Time Innovations, Inc.
  • 12. Standardizing the Adaptor/Transport NEEDED: Not so much a standard adaptor… …but: – A standard event meta-model Relevant OMG standards: UML, MOF, OCL, … – A ‘standard’ way to adapt to the existing Transports/Message Busses & information model Using the same Adaptor technology will not allow CEP engines to “interoperate” Relevant OMG standards: DDS, CORBA Notification Service Communicate != Interoperate 12 © 2007 Real-Time Innovations, Inc.
  • 13. Requirements on a CEP Message Bus Fit to the CEP information Model – CEP engines need access to data regardless of its source – CEP operates on structured data, not opaque messages Performance & Scalability – CEP systems are event-driven – CEP operates on streaming data and has low-latency & high- throughput requirements Configurability, QoS, Filtering & Services – CEP is deployed in critical systems that be robust to failures – CEP weaves streams with different QoS requirements (updates rates, priority) – CEP often needs access to only a subset of the information 13 © 2007 Real-Time Innovations, Inc.
  • 14. DDS: The best “message bus” for CEP? Fit to the CEP information Model – DDS is Data-Centric, not message centric – Beyond messaging DDS also does “state management” – DDS Supports Topic-Based and Content-Based Subscriptions – DDS built-in Window/Time selectors delivers *only* relevant data Performance & Scalability – DDS offers notification-based APIs – DDS has the best performance (latency, throughput, jitter, scalability) of any standard middleware technology Configurability, QoS, Filtering & Services – DDS Publish-Subscribe model delivers wherever needed – DDS has rich QoS to support real-time event-driven systems (latency budget, priority, etc.) – DDS Built-in Fault-Tolerance Mechanism allow for redundant sources of data – DDS built-in services Persistence and Historical Data Services ensures relevant data is never lost 14 © 2007 Real-Time Innovations, Inc.
  • 15. #1 DDS Data-Centric Model “Global Data Space” generalizes Subject-Based Addressing – Data objects addressed by DomainId, Topic and Key – Domains provide a level of isolation – Topic groups homogeneous subjects (same data-type & meaning) – Key is a generalization of subject Key can be any set of fields, not limited to a “x.y.z …” formatted string – Data Structure is known by the middleware Data Reader Data Writer Topic Data Reader Data Writer Data Reader Data Writer 15 © 2007 Real-Time Innovations, Inc.
  • 16. #1 DDS Data-Centric Model “Global Data Space” generalizes Subject-Based Addressing – Data objects addressed by DomainId, Topic and Key – Domains provide a level of isolation – Topic groups homogeneous subjects (same data-type & meaning) – Key is a generalization of subject Key can be any set of fields, not limited to a “x.y.z …” formatted string – Data Structure is known by the middleware Data Reader Data Writer Key (subject) Data Reader Data Writer Data Reader Data Writer 16 © 2007 Real-Time Innovations, Inc.
  • 17. #1 DDS Data-Centric Model “Global Data Space” generalizes Subject-Based Addressing – Data objects addressed by DomainId, Topic and Key – Domains provide a level of isolation – Topic groups homogeneous subjects (same data-type & meaning) – Key is a generalization of subject Key can be any set of fields, not limited to a “x.y.z …” formatted string – Data Structure is known by the middleware Data Reader Data Writer Data Object Data Reader Data Writer Data Reader Data Writer 17 © 2007 Real-Time Innovations, Inc.
  • 18. Subscriptions: By Topic, Subject, Content Topic: “Market Data” Key Fields Other Fields Payload Field Source Symbol Type Exchange Volume Bid Ask … Value * * * * * Topic: “Order Entry” Key Fields Other Fields Field Symbol Type Exchange OrderNumber OrderKind Stop Limit … Value * * NYSE * Subject Filter (for a Reader) Topic: “Market Data” Key Fields Other Fields Field Source Symbol Type Exchange Payload Value REUTERS * EQ NYSE Volume > x, Ask < y 18 © 2007 Payload Filter (for a Reader) Subject Filter (for a Reader) Real-Time Innovations, Inc.
  • 19. DDS communications model Data Domain Data Domain New Writer Participant Reader Participant “Alarm” Got new “Alarm” subscriber! data Offered Offered Listener QoS Listener QoS Participants scope the global data space (domain) Topics define the data-objects (collections of subjects) Writers publish data on Topics Readers subscribe to data on Topics QoS Policies are used configure the system Listeners are used to notify the application of events 19 © 2007 Real-Time Innovations, Inc.
  • 20. Demo: Concepts Start demo Display Area: Shows state of objects Topics – Square, Circle, Triangle – Attributes Data types (schemas) – Shape (color, x, y, size) Color is instance Key – Attributes Shape & color used for key QoS – Deadline, Liveliness – Reliability, Durability – History, Partition Control Area: – Ownership 20 Allows selection of objects and Real-Time Innovations, Inc. © 2007 QoS
  • 21. QoS: Quality of Service Standardized Middleware QoS semantics QoS Policy QoS Policy DURABILITY USER DATA HISTORY (per subject) TOPIC DATA READER DATA LIFECYCLE GROUP DATA WRITER DATA LIFECYCLE PARTITION LIFESPAN PRESENTATION ENTITY FACTORY DESTINATION ORDER RESOURCE LIMITS OWNERSHIP RELIABILITY OWNERSHIP STRENGTH TIME BASED FILTER LIVELINESS DEADLINE LATENCY BUDGET CONTENT FILTERS TRANSPORT PRIORITY 21 © 2007 Real-Time Innovations, Inc.
  • 22. Demo: Quality of Service (QoS) Start demo Writers and readers state Their needs Topics – Square, Circle, Triangle – Attributes Data types (schemas) – Shape (color, x, y, size) Color is instance Key – Attributes Shape & color used for key QoS – Deadline, Liveliness – Reliability, Durability – History, Partition – Ownership RTI DDS delivers 22 © 2007 Real-Time Innovations, Inc.
  • 23. DDS: The best “message bus” for CEP? #1 Fit to the CEP information Model – DDS is Data-Centric, not message centric – DDS Supports Topic-Based and Content-Based Subscriptions – DDS built-in Window/Time selectors delivers *only* relevant data #2 Performance & Scalability – DDS offers notification-based APIs – DDS has the best performance (latency, throughput, jitter, scalability) of any standard middleware technology #3 Configurability, QoS, Filtering & Services – DDS Publish-Subscribe model delivers wherever needed – DDS has rich QoS to support real-time event-driven systems (latency budget, priority, etc.) – DDS Fault-Tolerance Mechanism allows for redundant sources of data – DDS built-in services Persistence and Historical Data Services ensures relevant data is never lost 23 © 2007 Real-Time Innovations, Inc.
  • 24. Data-Distribution and Real-Time Messaging Technologies and Standards Web Services Java RTSJ (soft RT) RTSJ (hard RT) Java/RMI Java/JMS CORBA RT CORBA Data Distribution Service / DDS MPI Non-real-time Soft real-time Hard real-time Extreme real-time 24 © 2007 Real-Time Innovations, Inc. Adapted from NSWC-DD OA Documentation
  • 25. Latency – (Linear Scale) IBM HS20 blades Dual 2.8 GHz Xeon, 1 GB RAM Gigabit Ethernet DDS/JMS/Notification Service Comparison - Latency 2500 2000 DDS JMS Notification Service 1500 1000 500 0 16 32 64 128 256 512 1024 2048 4096 8192 16384 32768 65536 Message Size (bytes) Adapted from Vanderbilt presentation at July 2006 OMG Workshop on RT Systems 25 © 2007 Real-Time Innovations, Inc.
  • 26. Jitter – (Linear Scale) DDS/CORBA Notification Service Comparison - Jitter 100 DDS/JMS/CORBA Notification Service Comparison - Jitter Standard Deviation (usecs) 80 2000 1800 DDS JMS Notification service 60 Standard Deviation (usecs) 1600 1400 40 DDS JMS Notification service 1200 1000 20 800 600 0 400 16 32 64 128 256 512 1024 2048 4096 8192 16384 32768 65536 200 Message Size (bytes) 0 16 32 64 128 256 512 1024 2048 4096 8192 16384 32768 65536 Message Size (bytes) Source: Vanderbilt presentation at July 2006 OMG Workshop on RT Systems 26 © 2007 Real-Time Innovations, Inc.
  • 27. DDS : Low Latency and Jitter Latency and Jitter on Unloaded Network 400 Latency (microseconds) 350 300 Maximum 250 99.99% 200 99% 150 Median Minimum 100 50 0 32 64 128 256 512 1024 2048 4096 8192 Message/Data Size (bytes) Reliable, ordered delivery over Gigabit Ethernet between 2.0 GHz Opteron processors running 32-bit Red Hat Enterprise Linux 4.0 27 © 2007 Real-Time Innovations, Inc.
  • 28. DDS: Low Overhead Enables High Throughput 70,000 1000 900 60,000 800 50,000 700 Megabits per Second Updates per Second 600 40,000 500 30,000 400 20,000 300 200 10,000 100 0 0 16 32 64 128 256 512 1024 2048 4096 8192 16384 32768 Message/Data Size Reliable, ordered delivery over Gigabit Ethernet between 2.0 GHz Opteron processors running 32-bit Red Hat Enterprise Linux 4.0 28 © 2007 Real-Time Innovations, Inc.
  • 29. DDS: Scalable Performance (Confirmed Reliability) 60,000 50,000 Point-to-Point Updates per Second 40,000 1-1 1-10 1-24 30,000 20,000 10,000 0 16 32 64 128 256 512 1024 Message/Data Size (bytes - without batching) Reliable, ordered delivery over Gigabit Ethernet between 2.0 GHz Opteron processors 29 running 32-bit Red Hat Enterprise Linux 4.0 © 2007 Real-Time Innovations, Inc.
  • 30. DDS operates without brokers DDS Broker-based Middleware No Brokers => Better Performance & Determinism + Increased Robustness 30 © 2007 Real-Time Innovations, Inc.
  • 31. DDS: The best “message bus” for CEP? #1 Fit to the CEP information Model – DDS is Data-Centric, not message centric – DDS Supports Topic-Based and Content-Based Subscriptions – DDS built-in Window/Time selectors delivers *only* relevant data #2 Performance & Scalability – DDS offers notification-based APIs – DDS has the best performance (latency, throughput, jitter, scalability) of any standard middleware technology #3 Configurability, QoS, Filtering & Services – DDS Publish-Subscribe model delivers wherever needed – DDS has rich QoS to support real-time event-driven systems (latency budget, priority, etc.) – DDS Fault-Tolerance Mechanism allows for redundant sources of data – DDS built-in services Persistence and Historical Data Services ensures relevant data is never lost 31 © 2007 Real-Time Innovations, Inc.
  • 32. #3 QoS and Powerful Services – Redundancy & QoS Policy QoS Policy Failover DURABILITY USER DATA – Persistent Data HISTORY (per subject) TOPIC DATA – Last value cache READER DATA GROUP DATA LIFECYCLE – Historical cache WRITER DATA PARTITION LIFECYCLE LIFESPAN PRESENTATION ENTITY FACTORY DESTINATION ORDER RESOURCE LIMITS OWNERSHIP RELIABILITY OWNERSHIP STRENGTH TIME BASED FILTER LIVELINESS DEADLINE LATENCY BUDGET CONTENT FILTERS TRANSPORT PRIORITY 32 © 2007 Real-Time Innovations, Inc.
  • 33. Ownership and High Availability Producer / Writer I1 Prim strength=10 ary Topic T1 Producer / Writer I1 Backup strength=5 I2 Primary I1 I2 Producer / Writer I2 Backup strength=1 Owner determined per subject Only extant writer with highest strength can publish a subject (or topic for non-keyed topics) Automatic failover when highest strength writer: – Loses liveliness – Misses a deadline – Stops writing the subject Shared Ownership allows any writer to update the subject 33 © 2007 Real-Time Innovations, Inc.
  • 34. Data Persistence A standalone service that persists data outside of the context of a DataWriter Data Data Writer Data Writer Reader Data Global Reader Data Space Persistence Persistence Service Service Permanent Permanent Storage Storage 34 © 2007 Real-Time Innovations, Inc.
  • 35. Conclusion To get the best performance from your CEP you need the best message bus DDS is a natural fit for CEP: – The Data-Centric Pub-Sub information model is an excellent match to the CEP structured event model – DDS supports many of the CEP use-cases and QoS as first-class citizens – DDS offers the best performance and latency of any middleware standard 35 © 2007 Real-Time Innovations, Inc.