1. Davis Social Links S. Felix Wu Computer Science Department University of California, Davis wu@cs.ucdavis.edu http://www.cs.ucdavis.edu/~wu/

2. Internet Architecture & Routing Applications with Tests

3. Internet Architecture & Routing • Any identity (email address, IP, url) can communicate with any one else. • Email, web, bittorrent, warcraft, skype…

4. Social-Control Routing Applications with Tests 3 2 1

7. The value of the “Network” • A concern about a network losing its “value” • while we are unsure about how to quantify the true value…

8. Open Issues • What is the “value” of this social network? • How would this “value” be distributed and allocated to each individual peers? • MySpace, Facebook, LinkedIn didn’t define the “game” for network formation and value allocation. • But, it is important to design the game such that the OSN will eventually converge to a state to best support the communities.

9. Social Network Games

10. Fighter’s Club • A Coalition game ~ like Warcraft • Team members who are Facebook friends receive higher fighting powers • ~1400 new friendships established daily • ~10% of users with >95% friendships purely based on this game.

11. Facebook versus Personal Web Site • WWW: everybody can see it • Facebook: a selected set of people on your social network can see it

16. Activities, Knowledge Sharing, and Social Relationship Scalability, Privacy, Trust, Robustness, Performance…

17. Social Network Applications • Social-based collaborative filtering • Recommendation • Privacy-control • Advertising

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19. http://www.ebolamonkeyman.com/cheung.htm

20. Pick your favor Spam Filter(s)

21. This was considered a spam!

22. This was considered a spam! Sometimes, the cost of False Positive may be very high…

23. The Implication of FP’s • Spam-filters have to be conservative… • We will have some false negatives in our own inboxes. • We will use our own time to further filter.. • For me, 1~2 seconds per email

24. The emails I received just THIS morning…

25. You have about 1 second to decide……

29. “Social Spams” • They might not be spams as we often overlooked the social values of them!

30. Motivations • The value of social communication • To leverage • To protect

31. Communicate: [A, D] B D A C As long as “A” knows “D’s routable identity”

32. Hijackable Routable Identify

33. [A,D] + social context B D A C “A” has to explicitly declare if there is any social context under this communication activity with “D”!

34. Internet & Routable Identity • URL, IP address, email,…. • For ANYWHERE in the Internet • Without Routable Identity • Only available to certain parts of Social Networks • Using OSN to perform access control

36. Who is Salma?

37. Who is Salma?

38. Who is Salma?

39. My message to Salma

40. The Social Path(s)

41. “Optimality” • Not necessarily “the shortest path” • Social context consideration

42. More Examples

43. CyrusDSL • How do we accomplish these features? • How do we realize the concepts scaleable? • How will this system work against spams?

44. Just a couple issues … • How to establish the social route? • How would “A” know about “D” (or “D’s identity”) ? • How to maintain this “reputation network”? • MessageReaper: A Feed-back Trust Control System (Spear/Lang/Lu)

45. [A,D] + social context ?? B D A C “A” has to explicitly declare if there is any social context under this communication activity with “D”! But, “D” only cares if it is from “C” or not!

46. Search on “OSN” • How to get to from ? • The Small world model • 6 degree separation (Milgram, 1967) • “existence of a short path” • How to find the short path? (Kleinberg, 2000)

47. Re-wiring (Watts/Strogatz) Structured/Clustered 62 35 Trade off between D and Ccluster !

48. Routing in a Small World • Common question: do short paths exist? • Algorithmic question: assuming short paths exist. How do people find them?

49. Kleinberg’s results A decentralized routing problem • For nodes s,t with known lattice coordinates, find a short path from s to t. • At any step, can only use local information, • Kleinberg suggests a simple greedy algorithm and analyzes it:

50. Kleinberg’s Model • Use only Local information, except the distance to the target. • However, what is the “global distance” in cyber space? Yet, the assumption behind is that the “edges” depend on the “relative distance”.