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Issue No.11 - November (2011 vol.22)
pp: 1842-1850
Di Niu , University of Toronto, Toronto
Baochun Li , University of Toronto, Toronto
ABSTRACT
Most current-generation P2P content distribution protocols use fine-granularity blocks to distribute content to all the peers in a decentralized fashion. Such protocols often suffer from a significant degree of imbalance in block distributions, especially when the users are highly dynamic. As certain blocks become rare or even unavailable, content availability and download efficiency are adversely affected. Randomized network coding may improve block diversity and availability in P2P networks, as coded blocks are equally innovative and useful to peers. However, the computational complexity of network coding mandates that, in reality, network coding needs to be performed within segments, each containing a subset of blocks. In this paper, we quantitatively evaluate how network coding may improve content availability, block diversity, and download performance in the presence of churn, as the number of blocks in each segment for coding varies. Based on stochastic models and a differential equation approach, we explore the fundamental tradeoff between the resilience gain of network coding to peer dynamics and its inherent coding complexity. We conclude that a small number of blocks in each segment is sufficient to realize the major benefits of network coding, with acceptable coding cost.
INDEX TERMS
Peer-to-peer content distribution, generation-based network coding, peer dynamics, content availability, resilience.
CITATION
Di Niu, Baochun Li, "Analyzing the Resilience-Complexity Tradeoff of Network Coding in Dynamic P2P Networks", IEEE Transactions on Parallel & Distributed Systems, vol.22, no. 11, pp. 1842-1850, November 2011, doi:10.1109/TPDS.2011.53
REFERENCES
[1] T. Ho, R. Koetter, M. Medard, D.R. Karger, and M. Effros, "The Benefits of Coding over Routing in a Randomized Setting," Proc. IEEE Int'l Symp. Information Theory, 2003.
[2] C. Gkantsidis and P. Rodriguez, "Network Coding for Large Scale Content Distribution," Proc. IEEE INFOCOM '05, Mar. 2005.
[3] P.A. Chou, Y. Wu, and K. Jain, "Practical Network Coding," Proc. 41th Ann. Allerton Conf. Comm., Control and Computing, Oct. 2003.
[4] S. Deb, M. Médard, and C. Choute, "Algebraic Gossip: A Network Coding Approach to Optimal Multiple Rumor Mongering," IEEE Trans. Information Theory, vol. 52, no. 6, pp. 2486-2507, June 2006.
[5] D. Mosk-Aoyama and D. Shah, "Information Dissemination via Network Coding," Proc. IEEE Int'l Symp. Information Theory (ISIT '06), Oct. 2006.
[6] D. Leonard, V. Rai, and D. Loguinov, "On Lifetime-Based Node Failure and Stochastic Resilience of Decentralized Peer-to-Peer Networks," Proc. ACM SIGMETRICS Int'l Conf. Measurement and Modeling of Computer Systems (SIGMETRICS '05), June 2005.
[7] K.K. Ramakrishnan and R. Jain, "A Binary Feedback Scheme for Congestion Avoidance in Computer Networks," ACM Trans. Computer Systems, vol. 8, no. 2, pp. 158-181, May 1990.
[8] L. Massoulie and M. Vojnovic, "Coupon Replication Systems," Proc. ACM SIGMETRICS Int'l Conf. Measurement and Modeling of Computer Systems (SIGMETRICS '05), June 2005.
[9] S. Resnick, Adventures in Stochastic Processes. Birkhauser, 2002.
[10] C. Gkantsidis, J. Miller, and P. Rodriguez, "Anatomy of a P2P Content Distribution System with Network Coding," Proc. Fifth Int'l Workshop Peer-to-Peer Systems (IPTPS '06), 2006.
[11] R.W. Yeung, "Avalanche: A Network Coding Analysis," Comm. in Information and Systems, vol. 7, no. 4, pp. 353-358, 2007.
[12] S. Karlin and H.M. Taylor, A First Course in Stochastic Processes, second ed., Academic Press, Inc., 1975.
[13] T.G. Kurtz, "Approximation of Population Processes: CBMS-NSF Regional Conf. Series in Applied Math. SIAM, 1981.
[14] G. Tan and S.A. Jarvis, "Stochastic Analysis and Improvement of the Reliability of DHT-Based Multicast," Proc. IEEE INFOCOM, May 2007.
[15] P. Jacquet and W. Szpankowski, "Entropy Computations via Analytic Depoissonization," IEEE Trans. Information Theory, vol. 45, no. 4, pp. 1072-1081, May 1999.
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