Improving the Download Time of BitTorrent-like Systems

1. Improving the Download Time of BitTorrent-like Systems Chi-Jen Wu, Cheng-Ying Li, Jan-Ming Ho {cjwu, cyli, hoho}@iis.sinica.edu.tw Computer System and Communication Lab Institute of Information Science Academia Sinica

2. Agenda • Introduction • WLRF • Performance Evaluation • Conclusion and Future Work

3. The Popularity of BitTorrent • BitTorrent: The “one third of all Internet traffic” phenomenon • Online users (BigChampagne) • 6.8 million in August 2004 • 9.6 million in August 2005 • Traffic volume in 2004 • 35% of Internet traffic was BitTorrent • 62% of all traffic was P2P related • 53% of the above traffic was BitTorrent • Traffic volume in 2005 • Approximately 71% of all Internet traffic was P2P traffic • BitTorrent made up over half of all P2P traffic. Source: CacheLogic

4. Raising BitTorrent-like Applications • Game patch and software update • Using BT as the underlying delivery mechanism • e.g., World of WarCraft (Blizzard) • Considerations • Individual user • Selfish • Download completion time • Service provider • Extensive • Total system elapsed time

5. Problem Definition • Problem: long-tailed distribution time • Long system elapsed time • Goal • Sell the cow and drink the milk • Improve the total system elapsed time • Maintain a fast download time for the individual user 0 2000 4000 6000 8000 10000 12000 14000 Time (second)

6. Overview of BitTorrent • BitTorrent uses swarming techniques • File is split into pieces • Users connect to other users to exchange available pieces • All BitTorrent nodes exchange pieces • Seeds: have all the pieces of the file • Peers: have some pieces • Tracker: coordinator of a BitTorrent swarm • Main function: gives list of peers to nodes • Keeps download/upload statistics • Information about the file (# of pieces, etc.,)

7. Key Features of BitTorrent • Peer selection • Enforces cooperation, “Tit-for-Tat” policy • Only uploads pieces to nodes that are willing to download their pieces to other nodes • Choking: ignores free-riders’ requests • Piece selection • Peers always select their neighbors’ rarest pieces to download • Ensures that the pieces won’t become extinct • Increases parallelism: nodes have pieces that other nodes need

8. Agenda • Introduction • WLRF • Performance Evaluation • Conclusion and Future Work

9. Basic Concept • Benefits for peers with more pieces • Finish downloading quickly • Benefits for peers with fewer pieces • Can exchange with peers that have the most pieces Allows peers with more pieces to depart first 4/5 5/5 1/5 3/5

10. System Model of Bittorent • Local rarest first strategy (LRF) • Peer selects the requested piece • Missing • With smallest number of copies in its neighbors

11. System Model WLRF • Weighty piece selection strategy (WLRF) • Peer selects a piece • Missing • With highest weight among its neighbors Piece requested from a peer with more finished pieces has high weight

12. Agenda • Introduction • WLRF • Performance Evaluation • Conclusion and Future Work

13. Experiment Evaluation • Scenario • Bandwidth distribution of peers

14. ExperimentEvaluation • Scale of network • From 500 to 5,000 peers • Evaluation metrics • Mean download time • Mean total elapsed download time • Improvement ratio

15. Average Download Completion Time

16. System Elapsed Time

17. CDF of Finished Peers LRF WLRF

18. Piece Inter-arrival Time

19. Agenda • Introduction • WLRF • Performance Evaluation • Conclusion and Future Work

20. Conclusion • We have proposed a new BitTorrent piece selection strategy for software updates/game patch services • Weighty piece selection strategy • Easy and simple to implement • Performs well in terms of • Mean download time • Total elapsed time • Ongoingwork • Optimal solution in terms of download time and total elapsed time

21. Thank You Chi-Jen Wu, Cheng-Ying Li, Jan-Ming Ho {cjwu, cyli, hoho}@iis.sinica.edu.tw Institute of Information Science Academia Sinica