This presentation gives a brief, semi-technical introduction to Data Distribution Service (DDS) technology from the Object Management Group. The focus is on the business benefits of the technology generally, not on RTI's implementation in particular.

1. DDS in a Nutshell
Data-Centric Architecture and the
Data Distribution Service
The Global Leader Rick Warren rick.warren@rti.com
in DDS Director of Technical Solutions
© 2011 Real-Time Innovations, Inc.

2. Stuff You Will Learn
DDS is data-centric messaging.
1. What is “data-centricity” anyway?
2. Why is it a good way to build and
integrate systems?
3. What’s special about DDS?
© 2011 Real-Time Innovations, Inc. 2

3. Data-Centricity by Example: Calendaring
Alternative Process #1:
1. Email: “Meeting Monday at 10:00.”
2. Email: “Meeting moved to Tuesday.”
3. Email: “Here’s dial-in info for meeting…”
4. You: “Where do I have to be? When?”
5. You: (sifting through email…)
© 2011 Real-Time Innovations, Inc. 3

4. Data-Centricity by Example: Calendaring
Alternative Process #2:
1. Calendar: (add meeting Monday at 10:00)
2. Calendar: (move meeting to Tuesday)
3. Calendar: (add dial-in info)
4. You: “Where do I have to be? When?”
5. You: (check calendar)
© 2011 Real-Time Innovations, Inc. 4

5. Data-Centricity by Example: FaceBook
Alternative Process #1:
 Use the FaceBook web site.
Alternative Process #2:
 The web site doesn’t exist.
 Deduce your friends’ information based on the
notifications FaceBook sends you.
© 2011 Real-Time Innovations, Inc. 5

6. What’s the Difference? State.
 Things have attributes and
characteristics “State” (“data”) is a
– The meeting will run 1:00–2:00 snapshot of those
in the conference room.
– My friend’s phone number is attributes and
555-1234 and he’s currently characteristics.
grooming his cat.
– The car is blue and is traveling
north from Sunnyvale at 65
mph.
 …whether they exist in the Best Practice:
real world, in the computer,
or both operate on state
 …whether or not we observe directly, not dialogs
or acknowledge them about state.
© 2011 Real-Time Innovations, Inc. 6

7. Data-Centric =
the part of you care about
Describing the world
as it is
at a certain point in time
Implication: State of the world can be maintained by
infrastructure, not each app
© 2011 Real-Time Innovations, Inc. 7

8. Not Data-Centric =
Saying anything else
 “Hey you: go do this.”
 “The thing changed in this way.”
Implication: State must be inferred, reconstructed,
managed by each app
(Sometimes called “message-centricity”:
focus on what’s said vs. what is)
© 2011 Real-Time Innovations, Inc. 8

9. Why is it better
to just describe the world?
 Reconstructing the state of the world is hard.
– Must infer based on all previous messages
– Maintaining all these messages is expensive
– Each app makes these inferences => duplicate effort
 People make mistakes.
– Many copies of state => may be different => bugs
vs.
– Uniform operations on state => fewer bugs
© 2011 Real-Time Innovations, Inc. 9

10. Why is it better (over time)
to just describe the world?
Consider integrating based on
Function
vs.
Stateful Data
…
© 2011 Real-Time Innovations, Inc. 10

11. Why is it better (over time)
to just describe the world?
 Computers are  Integration effort
stupid. doesn’t scale.
– Integrate based on what – Integrate at level of
to do function
=> must know => everything integrates
everything you might do with everything else
=> future extension => effort scales with
hard square of number of
– Integrate based on what apps
exists – Integrate at level of
=> do whatever you stateful data
like; no one else cares => everything integrates
=> future extension with common model
easy => effort scales with
number of apps
© 2011 Real-Time Innovations, Inc. 11

12. So it’s “better.” Who cares?
 Faster to implement
=> Save time and money
 Easier to integrate and update
=> Protect your investment
 More reliable systems
=> Protect your business
© 2011 Real-Time Innovations, Inc. 12

13. Before We Forget: the Definition
For example, data
structures in XSD
A data-centric architecture: or IDL file.
1. …is based on a data model that is: Calendar Event =
• Start Time
– Appropriately documented— • Duration
i.e. understandable by humans • Location
– Formally defined— • Organizer
i.e. understandable by machines
– Discoverable—i.e. can be found during execution
2. The data model is independent of any domain-specific
functionality / application.
– i.e. made of nouns, not verbs
3. The (instantiated) data model is the only authoritative
source of state in the system.
© 2011 Real-Time Innovations, Inc. 13

14. DDS: Observe & Respond to a Changing World
Other technologies that support data-centricity:
– Databases: SQL
– Web: HTTP (mostly)
 …assume the world changes slowly
Not scalable
 …use network resources inefficiently 100 apps => 100x load
 …are highly centralized Slow
A few updates/sec
App App
Server
App App
State
App App
Unreliable
Failure here kills many apps 14

15. DDS: Observe & Respond to a Changing World
DDS:
 …allows you to observe frequent changes
 …uses network resources efficiently
 …is decentralized
Fast Scalable Managed Reliable
100,000’s updates/sec Load indep. # apps with QoS No single pt. failure
App App App App App App
State: Data Bus
© 2011 Real-Time Innovations, Inc. 15

16. DDS: Observe & Respond to a Changing World
Army JBC-P replaced home-grown messaging w/ DDS:
 Tracks 20x more objects with fewer failures
 …with 90+% less code
 …with 90+% lower CPU resources
Fast Scalable Managed Reliable
100,000’s updates/sec Load indep. # apps with QoS No single pt. failure
App App App App App App
State: Data Bus
© 2011 Real-Time Innovations, Inc. 16

17. How DDS Works
DDS is data-centric messaging.
That is,
 Messaging as a technique
 for distributing, accessing, and modifying stateful data
App App App App App App
Data
Data in Motion at Rest
e.g. DDS complements e.g. database
© 2011 Real-Time Innovations, Inc. 17

18. How DDS Works: Concepts & Terminology
 Domain: world you’re talking about
 Topic: group of similar things
Domain
– Similar structure (“type”) what
(e.g. medical devices)
– Similar way they change how
over time (“QoS”) when
 Instance: individual (changing) thing Topic
(e.g. EKG readings)
 Sample: snapshot of an instance at
a point in time
Instance
(e.g.
 DataWriter: source of information readings from
about part of the world (topic) EKG #42)
 DataReader: observer of part of the
world (topic)
© 2011 Real-Time Innovations, Inc. 18

19. Conclusion
 Data-centric architecture brings significant
business benefits
– Save time and money during initial development
– Leverage existing investments as solutions evolve
– Protect mission-critical functions with resilient, highly
available implementations
 DDS supports data-centricity for dynamic systems
– Develop event-driven systems based on open standards
– Communicate more efficiently:
• Deliver existing capability with fewer hardware resources
• Deliver greater capability with the same hardware resources
– Avoid single points of failure with distributed P2P topology
– Monitor and govern data delivery quality of service
© 2011 Real-Time Innovations, Inc. 19

20. Download a free evaluation of
RTI Data Distribution Service,
Thank You Professional Edition
from www.rti.com/downloads
© 2011 Real-Time Innovations, Inc. 20