TopBT: A Topology-Aware and Infrastructure-Independent BitTorrent Client

1. TopBT: A Topology-Aware and Infrastructure-Independent BitTorrent Client ShansiRen1, EnhuaTan2, TianLuo2, SongqingChen3, LeiGuo4, XiaodongZhang2 • 1MicrosoftCorporation • 2TheOhioStateUniversity • 3GeorgeMasonUniversity • 4Yahoo!Inc • IEEE INFOCOM 2010 1 1

2. Outlines • Motivation and Objectives • TopBT System Framework • Explore BT Peer Selection Policy • TopBT Experiments and Evaluation • Conclusion 2

3. Peer-to-Peer (P2P) Applications and Traffic • Popular P2P applications: • File sharing: BitTorrent, eDonkey, eMule • Voice-over-IP (VoIP): Skype • Streaming media: PPLive, PPStream, UUSEE, Joost • Online users • 6.8million in August 2004, 9.6 million in August 2005 (BigChampagne) • End of 2009, one BT client alone had 52 million users • Traffic volume • 73.8% is P2P, and 66.7% of P2P is BitTorrent (IPOQUE, 2007) Source: IPOQUE http://www.ipoque.com/resources/internet-studies/internet-study-2007 3

4. Peer-to-Peer Overlay and Underlay overlay Lack of communication Logic Layer Physical Layer underlay 4

5. P2P Overlay and Underlay Mismatch ISP C ISP D ISP A ISP B OH NYC CA VA • Isolated design: topology was not a design factor • Heavy Internet traffic • ISP shape P2P traffic due to the inefficiency caused by this mismatch • Non-trivial to bridge the gap • Some rely on Infrastructure • Some cannot retain speed 5

6. BitTorrent Working Process Peers in active set : unchoked swarm active set Other peers are choked active my node seed leecher peer set • traffic volume comes from active set; • active set is statically sized; • our research focuses on peer selections for the active set. 6

7. Issues & Concerns Take topology into consideration during peer selection • Users want to download fast • Internet Service Providers (ISPs) want to minimize generated traffic • How can we reduce unnecessary Internet traffic while retaining fast downloading speed? 7

8. Previous Client-Based BTs and Their Limits • Most existing BT clients adopt a peer selection solely based on downloading rates, and do not consider peer topology: Vuze, uTorrent, BitComet, etc • Generates a large amount of unnecessary traffic • BitTyrant uses both downloading and uploading rates to select peers (NSDI’07) • Downloading speed is fast • Still generates a lot of unnecessary traffic due to topology-unawareness 8

9. Infrastructure-Dependent Approaches and Their Limits We propose to build an topology-awareand infrastructure-independentBT system called TopBT. • [29] H. Xie, Y. R. Yang, A. Krishnamurthy, Y. Liu, and A. Silberschatz. P4P: Provider Portal for Applications. In Proceedings of the 2008 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (ACM SIGCOMM’08), Seattle, WA, USA, August 2008. • P4P http://www.powercam.cc/slide/886 Recent studies propose to utilize network layer informationin BT peer selections for fast download time and reduced traffic: • P4P [29]proposes that ISPs provides traffic, routing, and topology information to applications (SIGCOMM’08) • Relies on ISPs to provide information • Relies on ISPs to deploy customized interface • ISPs provides information difrerent from BT optimization objectives • Ono[7] proposes to utilize Content Distribution Networks (CDNs) to find close peers (SIGCOMM’08) • Relies on CDNs to provide information • Relies on large scale deployment of Ono clients • CDN metrics different from BT optimization objectives 9

10. Outlines • Motivation and Objectives • TopBT System Framework • Explore BT Peer Selection Policy • TopBT Experiments and Evaluation • Conclusion 10

11. TopBT Design Considerations • TopBT actively discovers peer proximities (close neighbors in underlay networks) • Routing hops in Autonomous Systems (ASes) • Routing hops in links • TopBT monitors downloading rates of close neighbors • TopBT uses a comprehensive metric that consider both routing proximities and transmission rates • Homepage • http://topbt.cse.ohio-state.edu/ 11

12. World Situation TopBT usage geo-distribution (as in March, 2010). 12

13. Screenshot

14. Screenshot (2)

15. TopBT System Framework AS-hop Examiner and Link-hop Examiner are responsible for discovering path proximity to connected peers. TopBT Components • Does NOT require major Internet infrastructure support • Does NOT require large deployment of its same type • Directly optimizedownloading time and traffic AS-hop Examiner Rate Monitor passively records download/upload throughput on each connection. Peer Selector Link-hop Examiner Peer Selector executes TopBT peer selection policy to choke/unchoke peers. Rate Monitor File Transfer Manager File Transfer Manager is the component responsible for downloading / uploading file pieces from/to peers, managing connections, and writing data to I/O devices. 15

16. AS-Hop and Link-Hop c b b a c Intra-AS routing within AS B b a a C Host h2 B Inter-AS routing between A and B d Host h1 A Intra-AS routing within AS A AS-hop: 1 Link-hop: 5 • Routing path can be at AS-level or link-level. • TopBT discovers both AS-level and link-level path proximities. 16

17. Discovering Path Proximities • Standard tools for Probing Connection Paths: • (TCP) Ping and Traceroute • Calculating Link-Hops and Autonomous System (AS)Hops (path proximity analysis) • Handling asymmetric routing paths 17

18. Probing Path with (TCP) Ping TTL TTL’ resp ping destination source • Packet initial TTL are predefined values . • Link-hop examiner checks response packet’s TTL value. • TCP Ping based on SYN/ACK or RST packets is used to • explore more remote hosts. 18

19. Calculating Link-Hops ping probe ping results 95% Internet paths Link-hops <= 30 Response Time-To-Live (TTL) value Initial TTL can be one of these typical values 255 UNIX 128 Windows NT/2000/XP 64 Linux Compaq Tru64 32 Windows 95/98/ME calculated link-hop 19

20. Calculating AS Hops traceroute probe Public servers (containing routing information) traceroute path raw traceroute path processed traceroute path BGP routing tables translated AS path (Border Gateway Protocol) de-duped AS path prefix-AS mapping table (Built offline) calculated distinct AS hops 20

21. Traceroute Probe Results Hop number, IP address, DNS name 1 169.229.62.1 2 169.229.59.225 3 128.32.255.169 4 128.32.0.249 5 128.32.0.66 6 209.247.159.109 7 * 8 64.159.1.46 9 209.247.9.170 10 66.185.138.33 11 * 12 66.185.136.17 13 64.236.16.52 inr-daedalus-0.CS.Berkeley.EDU soda-cr-1-1-soda-br-6-2 vlan242.inr-202-doecev.Berkeley.EDU gigE6-0-0.inr-666-doecev.Berkeley.EDU qsv-juniper--ucb-gw.calren2.net POS1-0.hsipaccess1.SanJose1.Level3.net ? ? pos8-0.hsa2.Atlanta2.Level3.net pop2-atm-P0-2.atdn.net ? pop1-atl-P4-0.atdn.net www4.cnn.com no DNS name resolution no response from router 21

22. Map IP Path to AS Path Berkeley AOL Traceroute output: (hop number, IP) 1 169.229.62.1 2 169.229.59.225 3 128.32.255.169 4 128.32.0.249 5 128.32.0.66 6 209.247.159.109 7 * 8 64.159.1.46 9 209.247.9.170 10 66.185.138.33 11 * 12 66.185.136.17 13 64.236.16.52 AS25 AS25 AS25 AS25 AS11423 AS3356 AS3356 AS3356 AS3356 AS1668 AS1668 AS1668 AS5662 Calren AS-hop: 5 Level3 CNN 22

23. Handling Asymmetric Traceroute Paths AS A Internet IP traffic AS B AS C destination source AS D Autonomous System (AS) Two connected hosts exchange AS-hop information! 23

24. Outlines • Motivation and Objectives • TopBT System Framework • Explore BT Peer Selection Policy • TopBT Experiments and Evaluation • Conclusion 24

25. Understanding BT Traffic Torrent File Summary • We use an instrumented client to collect the slice-level peer connection information once everyday for 7 days over over more than 100 Planet-Lab and residential hosts downloading from a number of torrents: 25

26. Policies to Select High Quality Peers • Traffic-oriented policies • Policy of selecting peers in the same AS • Policy of selecting peers with the lowest hops • Downloading speed-oriented policies • Downloading and uploading rates and their ratio • TopBT: comprehensive peer selection policy 26

27. Selecting Peers in the same AS • A few studies by Karagiiannis et al. (IMC’05) and Bindal et al. (ICDCS’06) suggest to select peers from the same AS. • Most other peers reside in different ASes. The client’s own AS does not have enough peers to be selected for fast downloading in most case. Heavy-tail: a few ASes have large # of peers, while the rest have only a few peers 27

28. Selecting Peers with Lowest Hops • The client can select peers with the lowest link (or AS) hops • Traffic reduction ratio is the difference between the current traffic and the traffic with lowest hop policy, divided by the current traffic with only connected peers with all available peers slice avg link-hop reduction ratio slice avg link-hop reduction ratio (>50%) nodes: save (>15%) mean link-hops (>50%) nodes: save (>50%) mean link-hops • Significant amount of network traffic can be reduced when selecting close peers to connect with. • We observe from our collected data that more than 50% of connections have AS-hops below 5. Thus, it is very likely for a host to find peers within the same AS or in nearby ASes that have less than 5 AS-hops. 28

29. Downloading Time Oriented Policy • Related factors: downloading rate (d-rate), or reciprocal uploading rate (u-rate) • Traditionally, unchoke peers with highest d-rate • “BitTyrant” (Piatek et al. NSDI’07) • consider both d-rate and u-rate • unchoke peers with highest d-rate/u-rate • best exploit uploading bandwidth 29

30. Routing Hop and d/u Speed Relationship (Same hops, different speed) #3000 #3800 Downloading rates have no strong correlation with routing hops d-rates and hops are widelydistributed 30

31. Peers are placed into 4 categories inTopBT Best Peers: Fast & Close Fastest & Far (NOT the best) Downloading Rate Worst Peers Slow & Closest Slow & Far (NOT the best) 1/(# of Hops)

32. Outlines • Motivation and Objectives • TopBT System Framework • Explore BT Peer Selection Policy • TopBT Experiments and Evaluation • Conclusion 32

33. Experiment Methodology • We deploy native BT, BitTyrant, and TopBT clients onto 150+ Planet-Lab (PL) and residential hosts. • We use a popular legal torrent that have a large number of non-PL peers. • We start native BT, BitTyrant, and TopBT in random order, and repeat the experiments once everyday in 7 days. 33

34. Traffic and Download Time • TopBT is slight faster than BitTyrant, and both are 25% faster than native BT • 30% TopBT hosts have avg AS-hop 15% less than native BT and BitTyrant • TopBT has much lower avg. link-hop than native BT and BitTyrant 34

35. Probing Delay and Overhead Probing at background, and does not affect download time • TopBT generates a peak number of ping messages in the beginning, and that number quickly drops to a few. Overall, TopBT is light-weight 35

36. Conclusion • The current BT applications have over-utilized the Internet resources because of the lack of communications between the overlay and the underlay. • The issue on how to reduce unnecessary Internet traffic without affecting user perceived downloading time remains challenging. • TopBT can achieve fast download time, at the same time reduce Internet traffic. • Weshow that on average TopBT can reduce about 25% downloadtraffic while achieving a 15% faster download speed comparedto several prevalent BT clients. 36

37. References • [3] R. Bindal, P. Cao, W. Chan, J. Medved, G. Suwala, T. Bates, and A. Zhang. Improving Traffic Locality in BitTorrent via Biased Neighbor Selection. In Proceedings of the 26th IEEE International Conference on Distributed Computing Systems (IEEE ICDCS’06), Lisbon, Portugal, July 2006. • [7] D. R. Choffnes and F. E. Bustamante. Taming the Torrent. In Proceedings of the 2008 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (ACM SIGCOMM’ 08), Seattle, WA, USA, August 2008. • [12] L. Guo, S. Chen, Z. Xiao, E. Tan, X. Ding, and X. Zhang. Measurements, Analysis, and Modeling of BitTorrent-like Systems. In Proceedings of the 2005 USENIX International Measurement Conference (USENIX IMC’05), Berkeley, CA, USA, October 2005. • [15] T. Karagiannis, P. Rodriguez, and K. Papagiannaki. Should Internet Service Providers Fear Peer-Assisted Content Distribution? In Proceedings of the 2005 USENIX International Measurement Conference (USENIX IMC’05), Berkeley, CA, USA, October 2005. • [21] M. Piatek, T. Isdal, T. Anderson, A. Krishnamurthy, and A. Venkataramani. Do Incentives Build Robustness in BitTorrent? In Proceedings of the 4th USENIX Symposium on Networked Systems Design and Implementation (USENIX NSDI’07), Cambridge, MA, USA, April 2007. • [25] S. Ren, L. Guo, and X. Zhang. ASAP: an AS-Aware Peer-Relay Protocol for High Quality VoIP. In Proceedings of 26th International Conference on Distributed Computing Systems (ICDCS’06), Lisboa, Portugal, July 2006. • [29] H. Xie, Y. R. Yang, A. Krishnamurthy, Y. Liu, and A. Silberschatz. P4P: Provider Portal for Applications. In Proceedings of the 2008 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (ACM SIGCOMM’08), Seattle, WA, USA, August 2008.