Talk presented at the 2016 Onward! conference colocated with splash in amsterdam. This work presents a framework for the spontaneous interaction (composition) of service components by learning services APIs. Upon discovery of services with a known API the composition is seamless.

1. TICSw @ncardoz
Emergent Software Services
Nicolás Cardozo
n.cardozo@uniandes.edu.co
Amsterdam November 2nd 2016

2. What this is all about2

3. What this is all about2
forward!

4. What this is all about2
forward!
pull push

5. What this is all about3
Env1 Env2

6. What this is all about3
Env1 Env2

7. What this is all about3
Env1 Env2

8. What this is all about3
Env1 Env2

9. What this is all about3
Env1 Env2

10. 4
Why should we care

11. 4
1. Complexity of systems is increasing (data, connections)
Why should we care

12. 4
Software systems are not isolated, they interact and
influence each other2.
1. Complexity of systems is increasing (data, connections)
Why should we care

13. 4
Software systems are not isolated, they interact and
influence each other2.
1. Complexity of systems is increasing (data, connections)
3. Users’ expectancy for personalization and interaction increases
Why should we care

14. Pervasive services5
Service S = compose(Serviceweather, Servicebike, Servicetraffic, Serviceroute)

15. Pervasive services5
Sbike
Sweather
Straffic
Sroute
Service S = compose(Serviceweather, Servicebike, Servicetraffic, Serviceroute)

16. Pervasive services5
Sbike
Sweather
Straffic
Sroute
Service S = compose(Serviceweather, Servicebike, Servicetraffic, Serviceroute)

17. Pervasive services5
What if components disappear
Knowledge about services in the
network is required
Sbike
Sweather
Straffic
Sroute
Service S = compose(Serviceweather, Servicebike, Servicetraffic, Serviceroute)

18. Disappearing components6
[Chen et al. goal-driven service composition in mobile pervasive computing. TSC 2016]
Service S = compose(Serviceweather, Servicebike, Servicetraffic, Serviceroute)

19. Disappearing components6
[Chen et al. goal-driven service composition in mobile pervasive computing. TSC 2016]
Service S = compose(Serviceweather, Servicebike, Servicetraffic, Serviceroute)

20. Disappearing components6
[Chen et al. goal-driven service composition in mobile pervasive computing. TSC 2016]
Service S = compose(Serviceweather, Servicebike, Servicetraffic, Serviceroute)

21. Disappearing components6
[Chen et al. goal-driven service composition in mobile pervasive computing. TSC 2016]
Service S = compose(Serviceweather, Servicebike, Servicetraffic, Serviceroute)

22. Mordor7

23. Enhanced routing for smarter cities8
People as
sensors
Air quality sensors
…
Noise sensors
[Nallur et al. Smart route planning using open data and participatory sensing. OSS 2015]

24. Enhanced routing for smarter cities8
People as
sensors
Air quality sensors
…
Noise sensors
[Nallur et al. Smart route planning using open data and participatory sensing. OSS 2015]

25. Enhanced routing for smarter cities8
People as
sensors
Air quality sensors
…
Noise sensors
[Nallur et al. Smart route planning using open data and participatory sensing. OSS 2015]

26. Definition of service components9
var noise = new Service({
inputs: [],
outputs: [[e1, nw1], [e2, nw2], ...],
qos: { "priority": 1 },
serviceInterface: {
service: function() {
_.each(this.graph.edges, function(e) {
client.get('fwk',function(err,reply){
this.outputs.push[e, reply];
});
});
}
},
combinator: function(serviceStates) {
_.each(serviceStates, function(state) {
_.each(state.data, function(edge, w) {
_.map(this.graph.edges, function(e) {
if(e.id == edge.id)
e.weight.push(w);
});
});
}, this);
return this.graph;
}
});

27. Components interaction10
Service1Service2
Spontaneous
discovery of services

28. Components interaction10
Service1Service2
Spontaneous
discovery of services
Type2
Outputs: {
O21,
O22,
…
}
Inputs: {
I21,
I22,
…
}
Type1
Outputs: {
O11,
O12,
…
}
Inputs: {
I11,
I12,
…
}

29. Components interaction10
Service1Service2
Spontaneous
discovery of services
Type2
Outputs: {
O21,
O22,
…
}
Inputs: {
I21,
I22,
…
}
Type1
Outputs: {
O11,
O12,
…
}
Inputs: {
I11,
I12,
…
}
when(Service1 of Type2) then compose(Service1, Service2)

30. Components interaction10
Service1Service2
Spontaneous
discovery of services
Type2
Outputs: {
O21,
O22,
…
}
Inputs: {
I21,
I22,
…
}
Type1
Outputs: {
O11,
O12,
…
}
Inputs: {
I11,
I12,
…
}
if(Outputs1 ⊆ Inputs2) then compose(Service1, Service2)
when(Service1 of Type2) then compose(Service1, Service2)

31. Components interaction10
Service1Service2
Spontaneous
discovery of services
Type2
Outputs: {
O21,
O22,
…
}
Inputs: {
I21,
I22,
…
}
Type1
Outputs: {
O11,
O12,
…
}
Inputs: {
I11,
I12,
…
}
if(Outputs1 ⊆ Inputs2) then compose(Service1, Service2)
when(Service1 of Type2) then compose(Service1, Service2)
push Service1+Service2

32. Components interaction11
var noise = new Service({
inputs: [],
outputs: [[e1, nw1], [e2, nw2], ...],
qos: { "priority": 1 },
serviceInterface: {
service: function() {
_.each(this.graph.edges, function(e) {
client.get('fwk',function(err,reply){
this.outputs.push[e, reply];
});
});
}
},
combinator: function(serviceStates) {
_.each(serviceStates, function(state) {
_.each(state.data, function(edge, w) {
_.map(this.graph.edges, function(e) {
if(e.id == edge.id)
e.weight.push(w);
});
});
}, this);
return this.graph;
}
});
discovery elements

33. Components interaction12
var routing = new Service({
inputs: [origin, destination, weightingData],
outputs: path,
qos: { "priority": function(p) {return p >=2;} },
conditions: function(interface, state) {
return this.qos.priority(state.priority);
},
serviceInterface: {
service: function() {
//build the path using the A* algorithm
//Edges in the city graph are weighted with weightingData
return astar.runAlgorithm();
}
},
});

34. Composing services13
var noise = new Service({
inputs: [],
outputs: [[e1, nw1], [e2, nw2], ...],
qos: { "priority": 1 },
serviceInterface: {
service: function() {
_.each(this.graph.edges, function(e) {
client.get('fwk',function(err,reply){
this.outputs.push[e, reply];
});
});
}
},
combinator: function(serviceStates) {
_.each(serviceStates, function(state) {
_.each(state.data, function(edge, w) {
_.map(this.graph.edges, function(e) {
if(e.id == edge.id)
e.weight.push(w);
});
});
}, this);
return this.graph;
}
});
Service combination

35. Composing services13
var noise = new Service({
inputs: [],
outputs: [[e1, nw1], [e2, nw2], ...],
qos: { "priority": 1 },
serviceInterface: {
service: function() {
_.each(this.graph.edges, function(e) {
client.get('fwk',function(err,reply){
this.outputs.push[e, reply];
});
});
}
},
combinator: function(serviceStates) {
_.each(serviceStates, function(state) {
_.each(state.data, function(edge, w) {
_.map(this.graph.edges, function(e) {
if(e.id == edge.id)
e.weight.push(w);
});
});
}, this);
return this.graph;
}
});
Service combination

36. Composing services14
Servicerouting
Servicenoise
q-value

37. Composing services14
Servicerouting
Servicenoise
q-value
Serviceless-cool-noise
q-value

38. Composing services14
Servicerouting
Servicenoise
q-value
push service
Serviceless-cool-noise
q-value

39. Ok, I’ll buy that. But
does it work?
15

40. Color Palette16
R
G
B
255
50
0

41. Color Palette16
R
G
B
∔
255 30
50 100
0 238

42. Color Palette16
R
G
B
∔
255 30
=
255
50 100 150
0 238 238

43. Color Palette17
1
10
100
0 2 4 6 8 10
No.ofemergentservices
No. of available service components
estimate
values
n+1

44. Color Palette18
C
Y
M
K
∔ ∔/

45. Color Palette19
1
10
100
1000
10000
0 10 20 30 40 50
No.ofemergentservices
No. of available service components
estimate
values
n+1

46. 20
P2
P1

47. 20
P2
P1

48. 20
P2
P1

49. 20
P2
P1

50. 20
P2
P1

51. 20
P2
P1

52. 20
P2
P1

53. 20
P2
P1

54. 21
No.ofemergentservices
1
10
100
1000
10000
100000
1000000
10000000
No. of available service components
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51
values
lower bound
upper bound
Poker hand
nP5
nC5

55. 22
Enhanced routing for smarter cities

56. 22
Mordor
Available Services:
1. Routing
2. Noise
Home automation servicesResource servicesUser preference servicesNavigation services
3. Noise routing
4. Air routing
5. Noise air routing
6. Air
7. Air noise routing
8. Noise air
9. Air noise
Enhanced routing for smarter cities

57. 22
Mordor
Available Services:
1. Routing
2. Noise
Home automation servicesResource servicesUser preference servicesNavigation services
3. Noise routing
4. Air routing
5. Noise air routing
6. Air
7. Air noise routing
8. Noise air
9. Air noise
Enhanced routing for smarter cities

58. 22
Mordor
Available Services:
1. Routing
2. Noise
Home automation servicesResource servicesUser preference servicesNavigation services
3. Noise routing
4. Air routing
5. Noise air routing
6. Air
7. Air noise routing
8. Noise air
9. Air noise
Enhanced routing for smarter cities

59. 22
Mordor
Available Services:
1. Routing
2. Noise
Home automation servicesResource servicesUser preference servicesNavigation services
3. Noise routing
4. Air routing
5. Noise air routing
6. Air
7. Air noise routing
8. Noise air
9. Air noise
Enhanced routing for smarter cities
Mordor
Available Services:
1. Routing
2. Noise
Home automation servicesResource servicesUser preference servicesNavigation services
3. Noise routing
4. Air routing
5. Noise air routing
6. Air
7. Air noise routing
8. Noise air
9. Air noise
10. Jogging routing
11. Biking routing
12. Noise jogging routing
13. Jogging biking routing

60. 22
Mordor
Available Services:
1. Routing
2. Noise
Home automation servicesResource servicesUser preference servicesNavigation services
3. Noise routing
4. Air routing
5. Noise air routing
6. Air
7. Air noise routing
8. Noise air
9. Air noise
Enhanced routing for smarter cities
Mordor
Available Services:
1. Routing
2. Noise
Home automation servicesResource servicesUser preference servicesNavigation services
3. Noise routing
4. Air routing
5. Noise air routing
6. Air
7. Air noise routing
8. Noise air
9. Air noise
10. Jogging routing
11. Biking routing
12. Noise jogging routing
13. Jogging biking routing
Duathlon

61. 23

62. Extracting semantics24
How to give mining to composed
services
‣ Semantic definitions
‣ Linguistic creation of meaning
‣ RDF in semantic web
‣ Viewpoints

63. Choice??!!25

64. Choice??!!25
The paradox of choice
✓ Classification by service type
✓ Using previously used services
‣ Learning from users’ behavior
‣ Filtering pointless compositions

65. Acceptance
26
Tolerance
‣ Comprehensive user empirical studies
‣ Techniques to be explored:
‣ Services explanation
‣ Improving the definition of conditions
for filtering

66. 27

67. @ncardoz
28
✓ Shifting the service computing model from a
pull-based model to a push-based model
Required developers’ knowledge about the
environment
Exploit more service components
“Service availability”

68. @ncardoz
28
Questions?
✓ Shifting the service computing model from a
pull-based model to a push-based model
Required developers’ knowledge about the
environment
Exploit more service components
“Service availability”