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Measurement-Based Optimization Techniques for Bandwidth-Demanding Peer-to-Peer Systems

Measurement-Based Optimization Techniques for Bandwidth-Demanding Peer-to-Peer Systems. T. S. Eugene Ng, Yang-hua Chu, Sanjay G. Rao, Kunwadee Sripanidkulchai and Hui Zhang Appeared in INFOCOM 2003. Presented By Felix Lam. Introduction.

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Measurement-Based Optimization Techniques for Bandwidth-Demanding Peer-to-Peer Systems

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  1. Measurement-Based Optimization Techniques for Bandwidth-Demanding Peer-to-Peer Systems T. S. Eugene Ng, Yang-hua Chu, Sanjay G. Rao, Kunwadee Sripanidkulchai and Hui Zhang Appeared in INFOCOM 2003 Presented By Felix Lam

  2. Introduction • Bandwidth-demanding P2P applications like file sharing or overlay multicast systems have performance depending on the selection of peers. • Goal • File Sharing - Find peer(s) with as high bandwidth as possible • Overlay multicast systems - Find peer that provides sufficient bandwidth for streaming  ShorterConvergence time

  3. Introduction • Three light-weight measurement-based techniques for peer selection • RTT Probing • Using a single 36 Byte ICMP ping message; the peer with smallest RTT is selected. • 10 KB TCP probing1 • Download 10 KB of data from each peer through a TCP connection; the peer with the shortest download time is selected. 1. Suggested in J. Jannotti, D. Gifford, K. L. Johnson, M. F. Kaashoek, and J. W. O, “Overcast:Reliable multicasting with anoverlay network,” Proc. Fourth Symposium on Operating System Design and Implementation (OSDI), Oct. 2000

  4. Introduction Cont’ • Bottleneck Bandwidth Probing (BNBW) • Use nettimer2 to measure BNBW to each candidate peer; the peer with the largest BNBW is selected 2. K. Lai and M. Baker, “Nettimer: A tool for measuring bottleneck link bandwidth,” Proc. 3rd USENIX Symposium on InternetTechnologies and Systems, Mar. 2001.

  5. Introduction • Interesting Questions: • How well can each individual technique identify a peer with high TCP available bandwidth? • What is the fundamental limitations of a technique? • Can adaptive applications benefit from using the basic techniques? • Can multiple basic techniques be exploited simultaneously?

  6. Trace-based Analysis • Peer Traces Collection • Peers are chosen “randomly” from the Open Napster servers • Data collected from each peer • Total time to download 500KB of data from the peer via TCP • The time taken to download the initial 10KB of data • RTT of ten 36-byte pings to the peer • The bottleneck link bandwidth found using nettimer between CMU and the chosen peers ……

  7. Trace-based Analysis

  8. Trace-based Analysis • How is the analysis done? • In each experiment, 100 peers are chosen randomly • Then the 3 techniques are applied independently to select a peer • An optimality Ratio (O.R.) is computed as the TCP throughput of the selected peer divided by the TCP throughput of the best peer among the 100 peers. • 1000 experiments are done, the average O.R. for each method is reported

  9. How well does each technique perform? • 40% - 50% O.R. • 10KB Probe and BNBW are only a bit better than RTT probing  Unusually high correlation between delay and bandwidth, because network access tech. affects delay

  10. Limitations of Basic Techniques • Inherent Difficulty of Peer Selections Significant performance drop by selecting a slightly lower ranked peer

  11. Limitations of Basic Techniques • Peer Selection or Peer Elimination? • To answer this, in each experiment, we choose the worst and the best N peers respectively, and compare the accuracy versus N

  12. Limitations of Basic Techniques • Inability to Differentiate Good Peers • Progressively remove 5% of the worst peers at a time • O.R. does not improve even when there are only good peers

  13. >80 % given 5 trials Limitations of Basic Techniques • Using Basic Techniques in Adaptive Applications • Adaptively select peers based on past observation on TCP throughput (e.g. changing parents in overlay multicast streaming applications) • Remove 95 or 90 worst performing peers, and find out the best performing peers based on observation on the TCP throughputs of the remaining peers

  14. Limitations of Basic Techniques • Complementarity Analyses of Basic Techniques • From the results, clearly the three can complement each other, in order words, they seldom select “good” peers at the same time. • If we follows the recommendation of the most successful technique among the three, O.R. of 0.73 can be achieved

  15. Limitations of Basic Techniques • Complementarity Analyses of Basic Techniques (Cont’) • However, it consumes a lot of time to perform all 3 types of probing techniques on all 100 candidates • Can we first use RTT probing to eliminate 95 worst peers and perform the 10KB and BNBW probing on the remaining 5 peers? • By doing so, we get O.R. of 0.68 < 0.73 • A little trade-off between the selection performance and probing overhead

  16. Joint Ranking improve the O.R. • Adopting RTT filtering • is a good choice to probing overhead • Still far from the theoretically possible O.R. of 0.82 (oracle) Application Case Studies • Media File Sharing • Assume the entire media file is downloaded from the chosen peer  no retrial • Joint Ranking • Sum up the rank values of 2 or more techniques; choose the peer with lowest sumed rank

  17. Application Case Studies • Overlay Multicast Streaming • Extend from the Narada3overlay multicast protocol, and test with a Internet testbed with 29 hosts 3. Y. Chu, S. G. Rao, S. Seshan, and H. Zhang, “Enabling conferencing applications on the Internet using an overlay multicast architecture,” Proc. ACM SIGCOMM, August 2001.

  18. Application Case Studies • Overlay Multicast Streaming (Cont’) • Can Joint Ranking further improve? • No significant improvement brought by Joint-Ranking • Using slightly better peer selection technique cannot bring significant improvement to adaptive applications • The key is to make quick adaptation decisions based on useful hints like RTT.. etc.

  19. Conclusion • First study of light-weight measurement techniques on peer-to-peer applications • Key insights • Peer selection is inherently challenging problem • With light-weight measurements, the performance of peer selection can improve significantly • The techniques work better in eliminating bad peers than selecting good peers • With adaptive peer selection (e.g. in overlay multicast), the performance can be further enhanced by light-weight measurements • The techniques are highly complementary and can be combined to give better performance

  20. Comments • Pro • Very rich trace-based and internet-based experiment results to illustrate the performance of light-weight probing techniques. • Very useful and interesting discovery about the high correlation between RTT and bandwidth • Con • The discussions does not capture the high dynamicity of network bandwidth

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