Delay Bounds and Scalability for Overlay Multicast

  • György Dán
  • Viktória Fodor
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4982)


A large number of peer-to-peer streaming systems has been proposed and deployed in recent years. Yet, there is no clear understanding of how these systems scale and how multi-path and multihop transmission, properties of all recent systems, affect the quality experienced by the peers. In this paper we present an analytical study that considers the relationship between delay and loss for general overlays: we study the trade-off between the playback delay and the probability of missing a packet and we derive bounds on the scalability of the systems. We use an exact model of push-based overlays to show that the bounds hold under diverse conditions: in the presence of errors, under node churn, and when using forward error correction and various retransmission schemes.


Overlay multicast Scalability Delay Large-deviation theory 


  1. 1.
    Sung, Y.-W., Bishop, M., Rao, S.: Enabling contribution awareness in an overlay broadcasting system. In: Proc. of ACM SIGCOMM, pp. 411–422 (2006)Google Scholar
  2. 2.
    Liao, X., Jin, H., Liu, Y., Ni, L.M., Deng, D.: Anysee: Scalable live streaming service based on inter-overlay optimization. In: Proc. of IEEE INFOCOM (April 2006)Google Scholar
  3. 3.
    Magharei, N., Rejaie, R.: PRIME: Peer-to-peer Receiver drIven MEsh-based streaming. In: Proc. of IEEE INFOCOM (May 2007)Google Scholar
  4. 4.
    Massoulie, L., Twigg, A., Gkantsidis, C., Rodriguez, P.: Randomized decentralized broadcasting algorithms. In: Proc. of IEEE INFOCOM (2007)Google Scholar
  5. 5.
    Fodor, V., Dán, G.: Resilience in live peer-to-peer streaming. IEEE Communications Magazine 45(6) (June 2007)Google Scholar
  6. 6.
    ‘PPLive,” (June 2007),
  7. 7.
    “OctoShape,” (June 2007),
  8. 8.
    Hei, X., Liang, C., Liang, J., Liu, Y., Ross, K.W.: A measurement study of a large-scale P2P IPTV system. IEEE Trans. Multimedia 9(8), 1672–1687 (2007)CrossRefGoogle Scholar
  9. 9.
    Small, T., Liang, B., Li, B.: Scaling laws and tradeoffs in peer-to-peer live multimedia streaming. ACM Multimedia (October 2006)Google Scholar
  10. 10.
    Dán, G., Fodor, V., Karlsson, G.: On the stability of end-point-based multimedia streaming. In: Proc. of IFIP Networking, May 2006, pp. 678–690 (2006)Google Scholar
  11. 11.
    Dán, G., Fodor, V., Chatzidrossos, I.: Streaming performance in multiple-tree-based overlays. In: Proc. of IFIP Networking, May 2007, pp. 617–627 (2007)Google Scholar
  12. 12.
    Dán, G., Fodor, V., Chatzidrossos, I.: On the performance of multiple-tree-based peer-to-peer live streaming. In: Proc. of IEEE INFOCOM (May 2007)Google Scholar
  13. 13.
    Kumar, R., Liu, Y., Ross, K.W.: Stochastic fluid theory for P2P streaming systems. In: Proc. of IEEE INFOCOM (May 2007)Google Scholar
  14. 14.
    Dán, G., Fodor, V.: An analytical study of low delay multi-tree-based overlay multicast. In: Proc. of ACM P2P-TV (August 2007)Google Scholar
  15. 15.
    Lelarge, M., Liu, Z., Xia, C.H.: Asyumptotic tail distribution of end-to-end delay in networks of queues with self-similar cross traffic. In: Proc. of IEEE INFOCOM (March 2004)Google Scholar
  16. 16.
    Denuit, M., Genest, C., Marceau, É.: Stochastic bounds of sums of dependent risks. Insurance: Mathematics and Economics 25(1), 85–104 (1999)MathSciNetzbMATHGoogle Scholar
  17. 17.
    Schwartz, A., Weiss, A.: Large Deviations for Performance Evaluation: Queues, communication and computing. Chapman and Hall, Boca Raton (1995)Google Scholar
  18. 18.
    Padmanabhan, V.N., Wang, H.J., Chou, P.A.: Resilient peer-to-peer streaming. In: Proc. of IEEE ICNP, pp. 16–27 (2003)Google Scholar
  19. 19.
    Castro, M., Druschel, P., Kermarrec, A.-M., Nandi, A., Rowstron, A., Singh, A.: SplitStream: High-bandwidth multicast in a cooperative environment. In: Proc. of ACM SOSP (2003)Google Scholar
  20. 20.
    Setton, E., Noh, J., Girod, B.: Rate-distortion optimized video peer-to-peer multicast streaming. In: Proc. of ACM APPMS, pp. 39–48 (2005)Google Scholar
  21. 21.
    Bishop, M., Rao, S., Sripanidkulchai, K.: Considering priority in overlay multicast protocols under heterogeneous environments. In: Proc. of IEEE INFOCOM (April 2006)Google Scholar
  22. 22.
    Zegura, E.W., Calvert, K., Bhattacharjee, S.: How to model an internetwork. In: Proc. of IEEE INFOCOM, March 1996, pp. 594–602 (1996)Google Scholar
  23. 23.
    Veloso, E., Almeida, V., Meira, W., Bestavros, A., Jin, S.: A hierarchical characterization of a live streaming media workload. In: Proc. of ACM IMC 2002, pp. 117–130 (2002)Google Scholar
  24. 24.
    Feller, W.: An Introduction to Probability Theory and its Applications. John Wiley and Sons, Chichester (1966)zbMATHGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2008

Authors and Affiliations

  • György Dán
    • 1
  • Viktória Fodor
    • 1
  1. 1.ACCESS Linnaeus Centre, School of Electrical Engineering KTHRoyal Institute of TechnologyStockholmSweden

Personalised recommendations