The document discusses Data Distribution Service (DDS) as a data-centric messaging architecture that enhances system integration and efficiency by maintaining a unified state across applications. It emphasizes the benefits of data-centricity, including faster implementation, easier updates, and more reliable systems, while contrasting with message-centric approaches that rely on message reconstruction. By leveraging DDS, organizations can manage dynamic systems effectively, improving resource utilization and reducing development costs.

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