1. P4P: Towards Cooperation between P2P and ISPs Haiyong Xie (Yale) Arvind Krishnamurthy (U. Washington) Avi Silberschatz (Yale) Y. Richard Yang (Yale) 2007-7-25

2. P4PWG July Meeting 2 P2P Content Distribution Traffic volume: up to 60-70% of Internet traffic is contributed by P2P applications [cachelogic] Traffic pattern: random peering (e.g., BitTorrents) causes traffic spread across PoPs and domains Problems  Increased network resource usage (e.g., using bandwidth of more links)  Increased network operational costs  Degraded performance to other applications http://www.cachelogic.com

3. 2007-7-25 P4PWG July Meeting 3 Bandwidth Battle between ISPs and P2P The battle results in a lose-lose situation ISPs try to “manage” P2P traffic  Upgrade network infrastructure  Deploy P2P caching devices  Terminate connectivity  Rate limit P2P traffic P2P tries to evade from being captured  Uses random ports  Encrypts traffic

4. 2007-7-25 P4PWG July Meeting 4 Where is the Fundamental Problem? Traditional ISP application feedback/control:  Routing/traffic engineering (TE)  Rate control through congestion feedback (packet drops) Ineffective for P2P  due to highly dynamic, scattered traffic pattern caused by dynamic, unguided (network-oblivious) peer selection Objective: design a framework to enable better ISP and P2P cooperation

5. 2007-7-25 P4PWG July Meeting 5 Design Rationale Performance improvement  for both ISPs and P2P Scalability  support a large number of P2P users and networks in dynamic settings Privacy preservation Extensibility  Application-specific requirements  Tracker-based vs. trackerless P2P systems  Gossip among peers Incremental deploymentability ISP contribution for P2P acceleration

6. 2007-7-25 P4PWG July Meeting 6 The P4P Framework P4P: proactive provider participation for P2P; P2P for providers; provider portal for P2P, … Two components  Control plane iTrackers: an ISP portal for P2P and content providers Three levels:  Network status: e.g., network topology  ISP policy and guideline: e.g., traffic balance ratio for inter-AS peering links, time of day preference  ISP capabilities: e.g., QoS, CoS, ISP servers participation in content distributions  Data plane [optional] Routers on data paths provide fine-grained, ISP policy-based feedbacks, e.g., utilize TCP ECN bit or feedback fields in an overlay packet header

7. 2007-7-25 P4PWG July Meeting 7 P4P Control Path: Obtain Network Status/Policy An iTracker for each ISP. 1: Peer queries iTracker of local ISP to obtain network status/policy 2,3: Tracker-based: peer reports status/policy to appTracker; appTracker selects peering set considering both ISP status/policy and application requirements [4]: Trackerless: peers exchange information and make peering decisions ISP B ISP A appTracker a iTracker B iTracker A b 2 3 1 1 [4] 2 3

8. 2007-7-25 P4PWG July Meeting 8 P4P Control Path : Request Capability ISP B 5: appTracker [content provider] requests ISP B’s participation in content distribution 6: ISP B allocates servers to accelerate content distribution 7: appTracker includes ISP B’s servers in returned peering sets to peers ISP A appTracker a iTracker B iTracker A b 6 7 5 Note: this can be extended to handle trackerless systems, as we did in the previous slide appTracker/content provider requests ISP capabilities to accelerate content distribution.

9. 2007-7-25 P4PWG July Meeting 9 P4P Framework: Data Path [optional] Routers mark packets to provide faster, fine-grained feedbacks, e.g., virtual capacity to optimize multihoming cost and performance ISP BISP A a b Peers adjust traffic rates according to feedbacks

10. 2007-7-25 P4PWG July Meeting 10 Test Plan for P4P Measurement study with Pando (in progress) Evaluate P2P self-adaptation schemes (in progress)  Generate best practices for P2P design  Serve as comparison basis iTracker (in progress)  Network information (roughly completed)  ISP policy and guideline (in progress)  ISP capability (in progress) Data path (in progress) Evaluate P4P design with Pando and Verizon (in progress)

11. 2007-7-25 P4PWG July Meeting 11 Preliminary Results Simulations  Discrete-event simulation a module for modeling BitTorrent protocol a module for modeling underlying network topology and data transfer dynamics using TCP rate equation  Network topology: PoP-level AT&T and Abilene topologies  Network routing: OSPF routing Internet experiments  53 Internet2 nodes on PlanetLab  iTracker for Abilene network  Use OSPF routing to re-construct traffic load on Abilene links

12. 2007-7-25 P4PWG July Meeting 12 Evaluation – BitTorrent on Abilene Compared to P4P, native P2P can result in  2x download completion time  2x higher link utilization Native P2P can result in some peers experiencing very long download completion time Native P2P can result in much larger variance in link utilization

13. 2007-7-25 P4PWG July Meeting 13 Evaluation – BitTorrent on AT&T Compared to P4P, native P2P can result in  1.6x download completion time  3x higher link utilization Some peers can experience very long download completion time with native P2P Link utilization variance can be larger for native P2P

14. 2007-7-25 P4PWG July Meeting 14 Evaluation – Liveswarms on PlanetLab Liveswarms* is a P2P-based video streaming application, which adapts BitTorrent protocol to video streaming context Run liveswarms on 53 PlanetLab nodes for 900 seconds P4P and native liveswarms achieve roughly the same amount of throughput P4P reduces link load  Average link load saving is 34MB  Maximum average link load saving is 60% Native liveswarms:1Mbps P4P liveswarms: 432Kbps *Michael Piatek, Colin Dixon, Arvind Krishnamurthy, Tom Anderson. LiveSwarms: Adapting BitTorrent for end host multicast. Technical report: UW-CSE-06-11-01

15. 2007-7-25 P4PWG July Meeting 15 Contact and Acknowledgement For further details, please refer to our technical report Yale/DCS TR-1377 It is still a work-in-progress and changes rapidly Questions/comments are highly welcome:  Haiyong Xie (haiyong.xie@yale.edu)haiyong.xie@yale.edu  Y. Richard Yang (yry@cs.yale.edu)yry@cs.yale.edu Acknowledgements We would like to thank Charles Kalmanek (AT&T Labs), Marty Lafferty (DCIA), Doug Pasko (Verizon), Laird Popkin (Pando), Keith Ross (Polytechnic), Ke Xu (Tsinghua Univ.) for suggestions, discussions and feedback.