The document discusses research on geographic routing in social networks. It examines routing strategies using only local information on networks modeled from real-world call detail records. The strategies include depth-first search (DFS), selecting the geographically closest friend (GEO), and selecting the best connected friend (DEG). Experiments show these strategies can successfully route messages between random pairs in the networks, with performance varying based on network structure and error rate. Shorter path lengths are found when routing at the municipal level compared to the province level.

1. Geographic routing in
social networks
C. Herrera, T. Couronne, Z. Smoreda, C. M. Schneider, R.
M. Benito, M. C. González

4. very short paths exist

5. People were able to
find them

6. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

7. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

8. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

9. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

10. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

11. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

12. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

13. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

14. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

15. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

16. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

17. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

18. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

19. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

20. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

21. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

22. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

23. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

24. What’s been done so far?
network
models
Real-world
experiments
Simulation
on network
data

25. Take home message
Routing in a real world network using
only local information may be possible:
We need to understand the role of
geography in the social links

26. Pretty BIG Data
3 phone networks country scope during
6 month
Mutual links considered (at least one
interaction per direction)
User are geo-located to their most used
tower

27. Pretty BIG Data 1
0.1
0.01
network
0.001
France
P(k)
1e−04
Portugal
1e−05 Spain
1e−06
1e−07
1e−08
1 10 100 1000 10000
k

28. Long distance relationships?
-1.5<α<-1

29. More likely short...
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d (km)

30. Let’s route!
“City”=province (20 Portugal, 96
France, 52 Spain)
We try to deliver the message to the
city
Experiment conditions:
• 60K Random pairs
• Error if not delivered in 100
hops

31. Let’s route!
“City”=province (20 Portugal, 96
France, 52 Spain)
We try to deliver the message to the
city
Experiment conditions:
• 60K Random pairs
• Error if not delivered in 100
hops

32. Let’s route!
Proposed methods
DFS: we don’t send to others who already got
the message, in case everybody got, send back
to the first person who sent us the message
GEO: send to the friend geographically closest
to target
DEG: send to the best connected friend

33. Let’s route! france portugal spain
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l−1

34. Let’s route!
30
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25
network
● france
portugal
20 spain
<l>
algorithm
● routing−dfs
● routing−dfs−geo
15
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● ● routing−dfs−geo−deg
10
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1e−04 0.001 0.01 0.1 1
Error Rate

35. Let’s route!
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0.001 0.010 0.100
Relative Province Size

36. Let’s route!
“City”=municipality (305
Portugal, 3520 France, 8410
Spain)
We try to deliver the message to the
city
Experiment conditions:
• 60K Random pairs
• Error if not delivered in 100
hops

37. Let’s route!
●
40
network
● france
portugal
30 spain
<l>
algorithm
● routing−dfs
● routing−dfs−deg
● routing−dfs−geo
● routing−dfs−geo−deg
20
● ●
●
10
1e−04 0.001 0.01 0.1 1
Error Rate

38. Let’s route!
●
40
network
● france
portugal
30 spain
<l>
algorithm
● routing−dfs
● routing−dfs−deg
● routing−dfs−geo
● routing−dfs−geo−deg
20
● ●
●
10
1e−04 0.001 0.01 0.1 1
Error Rate

39. Let’s route!
●
40
network
● france
portugal
30 spain
<l>
algorithm
● routing−dfs
● routing−dfs−deg
● routing−dfs−geo
● routing−dfs−geo−deg
20
● ●
●
10
1e−04 0.001 0.01 0.1 1
Error Rate

40. Let’s route!
●
40
network
● france
portugal
30 spain
<l>
algorithm
● routing−dfs
● routing−dfs−deg
● routing−dfs−geo
● routing−dfs−geo−deg
20
● ●
●
10
1e−04 0.001 0.01 0.1 1
Error Rate

41. Let’s route!
●
40
network
● france
portugal
30 spain
<l>
algorithm
● routing−dfs
● routing−dfs−deg
● routing−dfs−geo
● routing−dfs−geo−deg
20
● ●
●
10
1e−04 0.001 0.01 0.1 1
Error Rate