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Performance in Decentralized Filesharing Networks

Performance in Decentralized Filesharing Networks. Theodore Hong Freenet Project. Styles of collaboration. Centralized model e.g. Napster global index held by central authority (single point of failure) direct contact between requestors and providers Decentralized model

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Performance in Decentralized Filesharing Networks

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  1. Performance in Decentralized Filesharing Networks Theodore Hong Freenet Project

  2. Styles of collaboration • Centralized model • e.g. Napster • global index held by central authority (single point of failure) • direct contact between requestors and providers • Decentralized model • e.g. Freenet, Gnutella • no global index – local knowledge only (approximate answers) • contact mediated by chain of intermediaries

  3. Key questions • Does it work? • can we find the data? • query success rates  length of query paths • Does it scale? • logarithmic / linear / polynomial • Is it robust? • participants are unreliable • different failure modes possible

  4. An abstract model • Can model the network as a graph:

  5. Querying the network • Answering a query means finding a path • source = requestor • destination = provider • A distributed search problem! • approximate global solution using local knowledge • same problem as IP routing

  6. The Freenet algorithm • Graph structure actively evolves over time • new links form between nodes • files migrate through network  adaptive routing

  7. Initial simulations • Ring topology, 1000 nodes:

  8. Initial simulations (cont’d)

  9. Why does it work? • The small-world model • Milgram: six degrees of separation • Watts: between order and randomness • short-distance clustering + long-distance shortcuts

  10. P(n) ~ 1/n1.5 Links in the small world • “Scale-free” link distribution • P(n) = 1/nk • most nodes have only a few connections • some have a lot of links

  11. Small-world links (cont’d) • Real-world examples • movie actors (Kevin Bacon game) • world-wide web • nervous system of wormC. elegans

  12. The importance of routing • Existence of short paths is not enough – they must be found • Adaptivity helps Freenet find good paths • Compare: a random-routing network

  13. Scalability • Real-world networks are much larger • nearly 400,000 downloads of Freenet • 50 million Napster users • How well does Freenet scale?

  14. Fault-tolerance • Unreliability is normal in peer-to-peer • Two types of failure: • random failure • targeted attack

  15. Random failure

  16. Targeted attack

  17. To do • Variable disk/bandwidth capacity • if you build it, will they come? • Participants leaving and re-entering • File lifetimes • “lifetime” is relative • relationship between ease of retrieval and popularity, size • impact of splitting and combining

  18. Conclusions • Local approximations can be good enough • Small-world model provides useful framework • Metrics to consider: • query pathlength • clustering coefficient • link distribution • Issues to consider: • scalability • fault tolerance under various scenarios

  19. For more information • “Performance” chapter in Peer-to-Peer • I. Clarke, O. Sandberg, B. Wiley, T.W. Hong, “Freenet: a distributed anonymous information storage and retrieval system,” in Workshop on Design Issues in Anonymity and Unobservability, ed. by H. Federrath. Springer: New York (2001)

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