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Neighbour selection strategies in BitTorrent- like Peer-to-Peer systems L.G. Alex Sung, Herman Li March 30, 2005 for CS856 Web Data Management University.

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Presentation on theme: "Neighbour selection strategies in BitTorrent- like Peer-to-Peer systems L.G. Alex Sung, Herman Li March 30, 2005 for CS856 Web Data Management University."— Presentation transcript:

1 Neighbour selection strategies in BitTorrent- like Peer-to-Peer systems L.G. Alex Sung, Herman Li March 30, 2005 for CS856 Web Data Management University of Waterloo

2 2 Outline Introduction Problem Statement Proposed Categorization Schemes Experimental Approach Experiment Designs

3 3 Introduction BitTorrent Highlights

4 4 Problem Statement Goal: Explore the effect of two neighbour-selection strategies on the efficiency in content distribution for BitTorrent-like Peer-to-Peer systems Proposed strategies: –Neighbour selection by network capacity –Neighbour selection by locality –Preserve some degree of randomness What is BT-like? Incentive-built P2P systems with Tit- for-Tat exchange strategy. (central server not required) Why BT-like? We expect later unstructured P2P systems are BT-like. (eg. eXeem)

5 5 Preserving Randomness Avoid power-law (Zipf) distribution of pieces: –Some pieces may be rare in one domain (capacity or locality), but popular in the other one –Even distribution of pieces increases the sustainability Randomness preserved by including some fraction of randomly chosen peers of a different domain Logarithmic scales on both axesLinear scales on both axes

6 6 Matching by Capacity Hypothesis: Matching peers according to capacity similarities improves efficiency due to the Tit-for-Tat exchange strategy When low ability peers are connected to high ability peers: –get pieces when they are being optimistic unchoked –get choked again very quickly as they cannot offer a good exchanging rate

7 7 Matching by Locality Hypothesis: Matching peers by locality: –Benefit from the lower network latency –Better utilization of bandwidth The topology of the overlay network better matches the underlying network In the case that the uploading capacity was not previously fully utilized: –maximize the uploading speed by exchanging with peers that are physically closer

8 8 Experimental Approach Run experiments on Planet Lab nodes Planet Lab nodes experience similar network phenomenon as real BT users Select a set of Planet Lab nodes that is representative of the user population Population capacity and locality based on: –A public tracker log for “Beyond Good and Evil” from Dec 03 to Mar 04 [1] NLNetherlands (Europe) % USUnited States % AUAustralia % CACanada % 82.46%

9 9 Experiment Designs Experiment 1: Categorization by upload / download rate – sensitivity to randomness –System throughput vs randomness Experiment 2: Categorization by upload / download rate – sensitivity to number of categories –System throughput vs number of categories Experiment 3: Categorization by peer locality –System throughput vs randomness Experiment 4: Combination of improvement schemes –Categorization uses both capacity and locality –System throughput vs randomness

10 10 Related work Anonymous BT with keyword search –eXeem (a commercial product w/ ads) –(IP is not shown directly in the GUI) Non-random peer set distribution –Based on content availability [2]

11 11 References 1.J.A. Pouwelse, P. Garbacki, D.H.J. Epema, H.J. Sips. The Bittorrent P2P File-sharing System: Measurements and Analysis. 4th International Workshop on Peer-to-Peer Systems (IPTPS'05), Feb Simon G. M. Koo, C. S. George Lee, Karthik Kannan: A Genetic-Algorithm-Based Neighbor-Selection Strategy for Hybrid Peer-to-Peer Networks. In Proc. of the International Conference On Computer Communications and Networks (ICCCN 2004), IEEE 2004, pages , October 2004.


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