1. Leveraging Social Networks for Increased BitTorrent Robustness Wojciech Galuba, Karl Aberer EPFL, Switzerland Zoran Despotovic, Wolfgang Kellerer Docomo Euro-Labs, Munich, Germany

2. 2 Motivation 1 BitTorrent relies on cooperative behavior But freeriding possible  15-80% of peers are freeriders Freerider

3. 3 Current solution: Tit-for-tat Tit-for-tat (TFT) strategy:  Reward good uploaders by giving them higher priority TFT defense ineffective:  Large-view exploit  Seeders don’t download  all peers look equal to seeders

4. 4 Friend-to-Friend (F2F) systems Source of the problem  In P2P nets everyone is a stranger A solution: connect to friends’ computers only  Reliable, stable identities Take advantage of existing social trust  Cooperation more likely Social network P2P network

5. 5 Motivation 2 How can we leverage the social network to solve freeriding? Is the social network a good content distribution medium? BitTorrent

6. 6 The social BitTorrent Approach  BitTorrent on top of a social network  Friends’ computers added to the peer list  Protocol unchanged Communication only along the social links  Mutually authenticated  Can be encrypted for privacy Friend discovery  We use a centralized friend server  Possible decentralized implementation: PGP Jabber/XMPP

7. 7 Freeriding disincentive User interface: Alice Upload/download: 1.2 Bob UL/DL: 2.5 Carol UL/DL: 0.9 Daniel UL/DL: 1.2 Eve UL/DL: 0.02 Users unlikely to freeride on friends Hmmm... I need to talk to Eve

8. 8 Evaluated systems BT – BitTorrent implementation  Using trackers to discover peers SBT – the social BitTorrent  Only friend connections HBT – hybrid implementation  Both on peer list: friend peers peers obtained from the trackers  Friend uploads have absolute priority

9. 9 Experimental setup Simulated in protopeer.net Tit-for-tat (TFT), downloaders ordered by:  TFT on: how much they upload  TFT off: how much they download 1024 peers, 25 MB file, single initial seeder Mixture of peers with 0.5, 1 and 2Mbit/s upload bandwidth Social net generated based on MSN Messenger data

10. 10 Social network alone is an efficient content distribution medium  Though: long-tail problem

11. 11 Social network alone is an efficient content distribution medium  Though: long-tail problem

12. 12 Swarm density Def: Fraction of peers in the social network interested in downloading a file Low swarm density  distribution graph becomes disconnected Source No access to source

13. 13 Low swarm density  many failed downloads Trackers (in BT and HBT) solve the problem

14. 14 Social links give HBT advantage only if swarm density > 2%

15. 15 Linear scaling with content size

16. 16 O(logN) scaling with the number of peers

17. 17 Open problems We assumed uniform distribution of interested peers  In reality interest clustered in social nets Even better performance? Content discovery  Can friends-of-friends be trusted? Social BT  geo locality  less inter-AS traffic?

18. 18 Conclusions Social network alone an efficient and scalable content distribution medium Social BitTorrent  Increased robustness to freeriding  As long as swarm density >2% F2F approach to content distribution:  Authenticated connections, trust  Increased privacy