A Generative Programming Approach to Developing Pervasive Computing Systems

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This document presents a generative programming approach to developing pervasive computing systems. It describes challenges in pervasive computing like heterogeneity, lack of structure, and dynamicity. It proposes addressing these through domain-specific languages to describe devices, architectures, and generate a programming framework and simulation support. This approach aims to guide development and ensure conformance while abstracting distributed aspects and supporting multiple expertise.

Technology

A Generative Programming
Approach to Developing Pervasive
Computing Systems

Damien Cassou, Benjamin Bertran, Nicolas Loriant and Charles Consel

GPCE'09

Pervasive Computing

●
heterogeneity
●
lack of structuring
●
dynamicity
●
multiple expertise
●
testing  hardware/software
 functionalities
 interfaces
4

Pervasive Computing

●
heterogeneity
●
lack of structuring
●
dynamicity
●
multiple expertise  implicit interactions
●
testing  no global reasoning
 multi-roles components

5

Pervasive Computing

●
heterogeneity
●
lack of structuring
●
dynamicity
●
multiple expertise  incremental deployment
●
testing  mobility
 entity malfunction

6

Pervasive Computing

●
heterogeneity
●
lack of structuring
●
dynamicity
●
multiple expertise  hardware
●
testing  network protocols
 middleware
 user needs
7

Pervasive Computing

●
heterogeneity
●
lack of structuring
●
dynamicity
●
multiple expertise  time consuming
●
testing  cost ineffective
 limited situations

8

Pervasive Computing

●
heterogeneity ●
Existing approaches
●
lack of structuring
●
general purpose
●
dynamicity
●
multiple expertise
●
partial
●
testing

9

1 Taxonomy

DSL to describe a hierarchy of devices
●
attributes
●
data gathered
●
actions supported

14

1 Taxonomy

device SmokeDetector (Location loc){
source Smoke;
}

struct Smoke {
boolean isDetected;
}

15

1 Taxonomy

device Sprinkler (Location loc) {
action OnOff;
}

action OnOff {
on(); off();
}

16

2 Architecture
DSL to instantiate a common
pervasive computing architectural pattern

18

2 Architecture

context SmokeDetected: boolean {
source Smoke from SmokeDetector;
}

context FireState: boolean {
context SmokeDetected;
context AverageTemperature;
}

20

2 Architecture

controller FireController {
context FireState;
action Activation on Alarm;
action OnOff on Sprinkler;
}

21

3 Generated programming
framework
●
generated from the description
●
dedicated to the application

in a
GPL!

22

3 Generated programming
framework
●
guides the implementation
●
abstracts the distributed back-end
●
provides high level support

in a
GPL!

23

3 Generated programming
framework

...
24

3 Generated programming
framework

●
interfaces
●
proxies
●
composites
●
support
➢
discovery
➢
RPC
●
and more

25

4 Application development

guided by the description
through the generated framework
26

4 Application development
controller FireController {
context FireState;
action OnOff on Sprinkler;
…
} architecture
framework

class MyFireCtrl extends FireController {
@Override
void fireStateChanged(boolean fire, Location loc) {
if (fire) {
discover(sprinklersWhere()…).on();
…
}
device discovery remote procedure call
…
} query language
}

user code
27

5 Generated simulation support
Editor

29

5 Generated simulation support
Runtime platform
no additional code!

30

Conclusion & Future work
●
From a small description of a ●
Non-functional properties
pervasive computing system ●
security
●
a generated programming ●
fault tolerance
framework
●
Further leveraging on existing
– to guide the development approaches/tools
– to ensure conformance
●
unit testing
●
a support for graphical
●
refactoring
simulation
●
Generalizing our approach to
●
a middleware abstraction
other domains
layer

31

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A Generative Programming Approach to Developing Pervasive Computing Systems

1. A Generative Programming Approach to Developing Pervasive Computing Systems Damien Cassou, Benjamin Bertran, Nicolas Loriant and Charles Consel GPCE'09

2. Pervasive Computing Systems 2

3. 3

4. Pervasive Computing ● heterogeneity ● lack of structuring ● dynamicity ● multiple expertise ● testing  hardware/software  functionalities  interfaces 4

5. Pervasive Computing ● heterogeneity ● lack of structuring ● dynamicity ● multiple expertise  implicit interactions ● testing  no global reasoning  multi-roles components 5

6. Pervasive Computing ● heterogeneity ● lack of structuring ● dynamicity ● multiple expertise  incremental deployment ● testing  mobility  entity malfunction 6

7. Pervasive Computing ● heterogeneity ● lack of structuring ● dynamicity ● multiple expertise  hardware ● testing  network protocols  middleware  user needs 7

8. Pervasive Computing ● heterogeneity ● lack of structuring ● dynamicity ● multiple expertise  time consuming ● testing  cost ineffective  limited situations 8

9. Pervasive Computing ● heterogeneity ● Existing approaches ● lack of structuring ● general purpose ● dynamicity ● multiple expertise ● partial ● testing 9

10. Our approach 10

11. Our approach 11

12. Fire management scenario 12

13. 13

14. 1 Taxonomy DSL to describe a hierarchy of devices ● attributes ● data gathered ● actions supported 14

15. 1 Taxonomy device SmokeDetector (Location loc){ source Smoke; } struct Smoke { boolean isDetected; } 15

16. 1 Taxonomy device Sprinkler (Location loc) { action OnOff; } action OnOff { on(); off(); } 16

17. 17

18. 2 Architecture DSL to instantiate a common pervasive computing architectural pattern 18

19. 2 Architecture 19

20. 2 Architecture context SmokeDetected: boolean { source Smoke from SmokeDetector; } context FireState: boolean { context SmokeDetected; context AverageTemperature; } 20

21. 2 Architecture controller FireController { context FireState; action Activation on Alarm; action OnOff on Sprinkler; } 21

22. 3 Generated programming framework ● generated from the description ● dedicated to the application in a GPL! 22

23. 3 Generated programming framework ● guides the implementation ● abstracts the distributed back-end ● provides high level support in a GPL! 23

24. 3 Generated programming framework ... 24

25. 3 Generated programming framework ● interfaces ● proxies ● composites ● support ➢ discovery ➢ RPC ● and more 25

26. 4 Application development guided by the description through the generated framework 26

27. 4 Application development controller FireController { context FireState; action OnOff on Sprinkler; … } architecture framework class MyFireCtrl extends FireController { @Override void fireStateChanged(boolean fire, Location loc) { if (fire) { discover(sprinklersWhere()…).on(); … } device discovery remote procedure call … } query language } user code 27

28. 5 Generated simulation support 28

29. 5 Generated simulation support Editor 29

30. 5 Generated simulation support Runtime platform no additional code! 30

31. Conclusion & Future work ● From a small description of a ● Non-functional properties pervasive computing system ● security ● a generated programming ● fault tolerance framework ● Further leveraging on existing – to guide the development approaches/tools – to ensure conformance ● unit testing ● a support for graphical ● refactoring simulation ● Generalizing our approach to ● a middleware abstraction other domains layer 31

Editor's Notes

#2: I would like to present our approach to ease development of pervasive computing applications through generation
#3: pervasive computing systems involve everyday objects and activities in highly dynamic environments. All objects are networked and must be able to communicate. This paradigm is also called ubiquitous computing or ambient intelligence.
#4: But, as with each technology, it introduces its own challenges
#11: from the description: abstract middleware guide implementation ensure conformance support graphical simulation
#12: detailed overview with the outline of the rest of talk
#19: a context aggregates date from devices and interprets it to make it application-specific. For example, a Fire context... a controller uses data from one or multiple contexts and take the decision to activate the devices.
#25: the detail of the generated methods are in the paper. underlined methods and classes are abstract
#26: the detail of the generated methods are in the paper. underlined methods and classes are abstract

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Editor's Notes