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Request Algorithms In Freenet Style Peer To Peer Systems
 

Request Algorithms In Freenet Style Peer To Peer Systems

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Request Algorithms In Freenet Style Peer To Peer Systems Request Algorithms In Freenet Style Peer To Peer Systems Presentation Transcript

  • Request Algorithms in Freenet-style Peer-to-Peer Systems
    • Jeff Lesh
    • Lewis & Clark College
    • Portland, OR USA
    • Dr. Jens Mache, Jason Guchereau, Melanie Gilbert,
    • Felix Ramli, Matt Willkensin
  • Overview
    • Introduction to Freenet
      • Performance issues
    • Modified Request Algorithms
      • Results
    • Conclusions
  • What is Freenet?
    • completely decentralized
    • forwards requests to one neighbor
    • dynamically changes the overlay network and replicates files on demand.
      • Adapts to network usage
      • Improves when used
    • Global storage space
  • Request Algorithm =Data Request =Data Return Node A References Data Store 225 - B 932 -M 940-R 925 930 931 Node D References Data Store 100 - G 101 - H 113 - J 099 111 113 Node B References Data Store 025 - X 115 - C 230 - F 224 225 233 Node C References Data Store 111 - D 112 - E 119 - L 115 118 120 111 - D 225 - B 932 -M 940-R 025 - X 115 - C 230 - F 111 - D 112 - E 119 - L 099 111 113 025 - X 111 - D 115 - C 230 - F 225 - B 932 -M 940-R Request Algorithm
    • These changes in the overlay network improves the performance of subsequent queries
    • Some caching as well.
  • Freenet’s design goals
    • Privacy
      • Privacy for information producers, holders, and consumers;
      • Resistance to information censorship;
    • Performance
      • High availability and reliability through decentralization; and
      • Efficient, scalable, and adaptive storage and routing.
  • This talk focuses on efficiency.
    • Our measure of efficiency is pathlength.
      • Important for:
        • Users - delay
          • Chance of slow links
        • Network – bandwidth usage
  • Our Questions
    • How good are the existing algorithms?
      • “As the network is used, pathlength decreases” [Hong’01].
      • But, this assumes 50% inserts and 50% requests.
    • Can we improve it?
  • Figure 2 50:50 vs. 99:1
  • Why does this happen?
    • Insert and request algorithms creates specialized references.
      • Insert does more.
    • Requests don’t change the overlay network if they fail (and they do a lot at first).
    • We want to change these weaknesses.
  • Small-world effect
    • The overlay network created by the routing tables is an example of a small-world network.
    • Specialization as well as references to nodes that have far different specialization is key.
    • Real-world example.
    • Also common in:
      • Social networks - film actor collaboration
      • Neural Networks - C. Elegans (worm)
      • Power Grid
      • [Duncan J. Watt et.al. Nature ‘98]
  • The Experiments
    • Aurora Simulator – written by Theodor Hong
    • It simulates nodes interacting with other nodes
    • Inserting and requesting existing documents and recording the number of hops it takes to find them.
    • The data we present is an average from 100 simulation runs.
  • Modified Request Algorithms
    • Learning from failed requests .
    • Announcing successful requests .
      • Breadth-random fashion
      • Breadth-neighbor fashion
  • Failed requests
    • As is they don’t add any short-cuts.
    • Our goal was to take advantage of the work already done up to the expiration of the HTL.
    • Short-cut from the requesting node to the last node’s data item with key closest to requested one.
  • Example
  • Successful Requests
    • The main idea is to add extra reference pointing to the fulfiller for each remaining HTL.
    • Breadth-random
    • Breadth-neighbor approach worked best.
      • Here is announces itself to its neighbors with key close to the one it fulfilled.
      • This promotes specialization.
  • Example - Successful Requests.
    • Reference Table
    • 155 Z
    • 202 B
    • 901 C
    • 912 H
    • 939 V
    Who to announce to? Data Store 900
  • Results
  • Conclusions
    • The original request algorithm is not very effective at changing the overlay network.
    • They way to improve the performance of Freenet is to enhance the small-world properties that it already has.
    • Our combined algorithm was able,in simulation, to lower the pathlength under 99 to 1 conditions from 225 to 25.
  • Backup Slides
  • Differences from distributed hash table.
    • Data is placed deterministically
      • Items located within bounded number of hops, but
      • Securing against attack, load balancing, and (for some) exploiting network proximity becomes more difficult.
    • Open source
      • We can modify, learn.
  • 50,000 Actions (99:1)
    • Original median pathlength: 2.94
    • Recycled
      • 100% : 6.25
      • 25% : 2.88