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Stefan Saroiu P. Krishna Gummadi Steven Gribble University of Washington

Characteristics of Current P2P File-Sharing Systems (with a brief excursion into network measurement tools). Stefan Saroiu P. Krishna Gummadi Steven Gribble University of Washington. Peer-to-Peer Frenzy. Both research and industrial excitement

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Stefan Saroiu P. Krishna Gummadi Steven Gribble University of Washington

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  1. Characteristics of Current P2P File-Sharing Systems(with a brief excursion into network measurement tools) Stefan Saroiu P. Krishna Gummadi Steven Gribble University of Washington

  2. Peer-to-Peer Frenzy • Both research and industrial excitement • CAN, Chord, Past, Tapestry, JXTA, Farsite, Publius, Morpheus, AudioGalaxy • Basic Premise • wide-area, distributed system • voluntary, ad-hoc, dynamic home-user peers exchange information (mostly large files) • Many proposals, yet nobody knows the participating peers’ characteristics and behavior

  3. Napster & Gnutella napster.com P P D S S Q P P P P R S S P R R Q P P Q Q P Q D P P Q P Napster Gnutella Q peer query P D file download R response server S

  4. Methodology 2 stages: • periodically crawl Gnutella/Napster • discover peers and their metadata • feed output from crawl into measurement tools: • bottleneck bandwidth – SProbe • latency – SProbe • peer availability – LF • degree of content sharing – Napster crawler

  5. Network Bandwidth Scenarios • Network measurements • Dynamic server/peer selection • P2P overlay formation • or application-level multicast • Placement of content replicas

  6. Network Bandwidth • Throughput: • number of transferred bytes during a fix interval of time • Available bandwidth: • the maximum attainable throughput of a newly started flow • Bottleneck bandwidth: • maximum throughput ideally obtained across the slowest link • Hard to measure: • throughput, available bandwidth • Easier to measure: • bottleneck bandwidth

  7. One-Packet Model probing packet Traversal Time 1 slope = bottleneck bandwidth Packet Size

  8. Packet-Pair Model packet size = bottleneck bandwidth Δt bottleneck bandwidth time dispersion proportional to bottleneck bandwidth

  9. Vital Properties of an Ideal Tool • Accurate • Fast: • 1 min/measurement too slow • Scalable: • flooding the network will not work • Works in Uncooperative Environments • can’t deploy software at both endpoints

  10. Properties of an Ideal Tool • Active: • existent traffic might not be suitable • TCP/UDP based: • ICMP heavily filtered • Cross-traffic resilient: • should detect and give up in the face of cross traffic • Works on Asymmetric Paths • Flexible to Bandwidth Changes • Controlled Evaluations

  11. Current Tools

  12. SProbe Uses TCP Tricks • From local host To remote host • No cooperation needed Local Remote SYN packet RST packet

  13. SProbe Uses TCP Tricks • From local host To remote host • No cooperation needed Local Remote SYN packet RST packet

  14. SProbe Uses TCP Tricks • From local host To remote host • No cooperation needed Local Remote SYN packet RST packet

  15. SProbe Uses TCP Tricks • From local host To remote host • No cooperation needed Local Remote SYN packet RST packet

  16. SProbe Uses TCP Tricks • From local host To remote host • No cooperation needed Local Remote SYN packet RST packet

  17. SProbe Uses TCP Tricks • From local host To remote host • No cooperation needed Local Remote SYN packet RST packet

  18. SProbe Uses TCP Tricks • From local host To remote host • No cooperation needed Local Remote SYN packet RST packet

  19. SProbe Uses TCP Tricks • From local host To remote host • No cooperation needed Local Remote SYN packet RST packet

  20. SProbe Uses TCP Tricks • From local host To remote host • No cooperation needed Local Remote SYN packet RST packet

  21. SProbe Uses TCP Tricks • From local host To remote host • No cooperation needed Local Remote SYN packet RST packet

  22. SProbe Uses TCP Tricks • From local host To remote host • No cooperation needed Local Remote SYN packet RST packet

  23. SProbe Uses TCP Tricks • From local host To remote host • No cooperation needed Local Remote SYN packet RST packet

  24. SProbe Uses TCP Tricks • From remote To local • Involuntary cooperation of application layer Local Remote (Web) HTTP Get request Data packet ACK (last data packet)

  25. SProbe’s Accuracy

  26. SProbe’s Accuracy

  27. More SProbe • Bottleneck Bandwidth • Latency • Availability (LF): • send a SYN packet • receive: • SYN/ACK – host active • RST – host inactive, but online • nothing – host offline

  28. P2P Characteristics • How many peers are “server-like”? • Who are the free-riders? • Do peers tend to lie? • How robust is the Gnutella overlay?

  29. P2P Characteristics • How many peers are “server-like”? • Who are the free-riders? • Do peers tend to lie? • How robust is the Gnutella overlay?

  30. Higher Downstream Bandwidths

  31. Most Peers have Cable Modem-like Bandwidths

  32. Yes, Lots of Cable Modems

  33. Closest 20% are 4X closer than furthest 20%

  34. Two horizontal bands – East Coast and Transoceanic Links

  35. Availability • Period probes yield data like: end start

  36. Availability • Period probes yield data like: • Divide into two periods • Keep segments that: • start in 1st period • end in 1st or 2nd periods • draw conclusion only on segments no larger than 2nd period end start 12 hours

  37. Median Session is about one hour (same for both systems)

  38. Gnutella/Napster Uptime

  39. P2P Characteristics • How many peers are “server-like”? • Who are the free-riders? • Do peers tend to lie? • How robust is the Gnutella overlay?

  40. Who Has the Files?

  41. Who Has the Files?

  42. Correlation of Free-Riding with B/W

  43. P2P Characteristics • How many peers are “server-like”? • Who are the free-riders? • Do peers tend to lie? • How robust is the Gnutella overlay?

  44. It’s all about incentive!

  45. Lack of Knowledge is Universal

  46. P2P Characteristics • How many peers are “server-like”? • Who are the free-riders? • Do peers tend to lie? • How robust is the Gnutella overlay?

  47. Power-Law Networks are here to Stay • Barabasi and Albert showed that networks which… • grow by continuous addition of new nodes • exhibit preferential attachment (likelihood of connecting to a node depends on the node’s degree) • …power-law distribution of vertex degree • Internet, WWW, Gnutella

  48. Resilience to Failures • Power-law networks (Cohen et al.): • very resilient in face of random node failures • a giant spanning cluster still exists • fairly resilient in face of cascading failures • very vulnerable in face of orchestrated attacks (towards high-degree nodes)

  49. Popular sites: • 212.239.171.174 • adams-00-305a.Stanford.EDU • 0.0.0.0 Gnutella 1771 hosts Fri Feb 16 05:21:52-05:23:22 PST

  50. 30% random failures 1771 – 471 – 294 hosts Fri Feb 16 05:21:52-05:23:22 PST

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