skip to main content
10.5555/1656980.1656984guideproceedingsArticle/Chapter ViewAbstractPublication PagesmiddlewareConference Proceedingsconference-collections
research-article
Free Access

Heterogeneous gossip

Published:30 November 2009Publication History

ABSTRACT

Gossip-based information dissemination protocols are considered easy to deploy, scalable and resilient to network dynamics. Load-balancing is inherent in these protocols as the dissemination work is evenly spread among all nodes. Yet, large-scale distributed systems are usually heterogeneous with respect to network capabilities such as bandwidth. In practice, a blind load-balancing strategy might significantly hamper the performance of the gossip dissemination.

This paper presents HEAP, HEterogeneity-Aware gossip Protocol, where nodes dynamically adapt their contribution to the gossip dissemination according to their bandwidth capabilities. Using a continuous, itself gossip-based, approximation of relative bandwidth capabilities, HEAP dynamically leverages the most capable nodes by increasing their fanout, while decreasing by the same proportion that of less capable nodes. HEAP preserves the simple and proactive (churn adaptation) nature of gossip, while significantly improving its effectiveness. We extensively evaluate HEAP in the context of a video streaming application on a testbed of 270 PlanetLab nodes. Our results show that HEAP significantly improves the quality of the streaming over standard homogeneous gossip protocols, especially when the stream rate is close to the average available bandwidth.

References

  1. K. Birman, M. Hayden, O. Ozkasap, Z. Xiao, M. Budiu, and Y. Minsky. Bimodal Multicast. TOCS, 17(2):41--88, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. M. Bishop, S. Rao, and K. Sripanidulchai. Considering Priority in Overlay Multicast Protocols under Heterogeneous Environments. In Proc. of INFOCOM, 2006.Google ScholarGoogle ScholarCross RefCross Ref
  3. T. Bonald, L. Massoulié, F. Mathieu, D. Perino, and A. Twigg. Epidemic Live Streaming: Optimal Performance Trade-Offs. In Proc. of SIGMETRICS, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. M. Castro, P. Druschel, A.-M. Kermarrec, A. Nandi, A. Rowstron, and A. Singh. SplitStream: High-Bandwidth Multicast in Cooperative Environments. In Proc. of SOSP, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Y.-H. Chu, S. Rao, and H. Zhang. A Case for End System Multicast. JSAC, 20(8):1456--1471, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. A. Demers, D. Greene, C. Hauser, W. Irish, J. Larson, S. Shenker, H. Sturgis, D. Swinehart, and D. Terry. Epidemic Algorithms for Replicated Database Maintenance. In Proc. of PODC, 1987. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. M. Deshpande, B. Xing, I. Lazardis, B. Hore, N. Venkatasubramanian, and S. Mehrotra. CREW: A Gossip-based Flash-Dissemination System. In Proc. of ICDCS, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. P. Eugster, R. Guerraoui, S. Handurukande, A.-M. Kermarrec, and P. Kouznetsov. Lightweight Probabilistic Broadcast. TOCS, 21(4):341--374, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. D. Frey, R. Guerraoui, A.-M. Kermarrec, M. Monod, and V. Quéma. Stretching Gossip with Live Streaming. In Proc. of DSN, 2009.Google ScholarGoogle ScholarCross RefCross Ref
  10. B. Garbinato, F. Pedone, and R. Schmidt. An Adaptive Algorithm for Efficient Message Diffusion in Unreliable Environments. In Proc. of DSN, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. R. Guerraoui, K. Huguenin, A.-M. Kermarrec, and M. Monod. On Tracking Freeriders in Gossip Protocols. In Proc. of P2P (to appear), 2009.Google ScholarGoogle ScholarCross RefCross Ref
  12. X. Hei, C. Liang, J. Liang, Y. Liu, and K. Ross. A Measurement Study of a Large-Scale P2P IPTV System. TMM, 9(8):1672--1687, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. M. Jelasity, A. Montresor, and O. Babaoglu. Gossip-Based Aggregation in Large Dynamic Networks. TOCS, 23(3):219--252, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. K. Jenkins, K. Hopkinson, and K. Birman. A Gossip Protocol for Subgroup Multicast. In Proc. of ICDCS Workshops, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. A.-M. Kermarrec, L. Massoulié, and A. Ganesh. Probabilistic Reliable Dissemination in Large-Scale Systems. TPDS, 14(3):248--258, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. P. Kyasanur, R. R. Choudhury, and I. Gupta. Smart Gossip: An Adaptive Gossip-based Broadcasting Service for Sensor Networks. In Proc. of MASS, 2006.Google ScholarGoogle ScholarCross RefCross Ref
  17. B. Li, Y. Qu, Y. Keung, S. Xie, C. Lin, J. Liu, and X. Zhang. Inside the New Coolstreaming: Principles, Measurements and Performance Implications. In Proc. of INFOCOM, 2008.Google ScholarGoogle Scholar
  18. H. Li, A. Clement, M. Marchetti, M. Kapritsos, L. Robinson, L. Alvisi, and M. Dahlin. FlightPath: Obedience vs Choice in Cooperative Services. In Proc. of OSDI, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. H. Li, A. Clement, E. Wong, J. Napper, I. Roy, L. Alvisi, and M. Dahlin. BAR Gossip. In Proc. of OSDI, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. C. Liang, Y. Guo, and Y. Liu. Is Random Scheduling Sufficient in P2P Video Streaming? In Proc. of ICDCS, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. L. Ma and W. Ooi. Congestion Control in Distributed Media Streaming. In Proc. of INFOCOM, 2007.Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. N. Magharei and R. Rejaie. PRIME: Peer-to-Peer Receiver-drIven MEsh-based Streaming. In Proc. of INFOCOM, 2007.Google ScholarGoogle Scholar
  23. V. Pai, K. Kumar, K. Tamilmani, V. Sambamurthy, and A. Mohr. Chainsaw: Eliminating Trees from Overlay Multicast. In Proc. of IPTPS, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. F. Picconi and L. Massoulié. Is There a Future for Mesh-Based live Video Streaming? In Proc. of P2P, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. PPLive. http://www.pplive.com.Google ScholarGoogle Scholar
  26. N. Spring, L. Peterson, A. Bavier, and V. Pai. Using Planetlab for Network Research: Myths, Realities, and Best Practices. OSR, 40(1):17--24, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Y.-W. Sung, M. Bishop, and S. Rao. Enabling Contribution Awareness in an Overlay Broadcasting System. CCR, 36(4):411--422, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. R. van Renesse, K. Birman, and W. Vogels. Astrolabe: A Robust and Scalable Technology for Distributed System Monitoring, Management, and Data Mining. TOCS, 21(2):164--206, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. V. Venkataraman, K. Yoshida, and P. Francis. Chunkyspread: Heterogeneous Unstructured Tree-Based Peer to Peer Multicast. In Proc. of ICNP, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. V. Vishnumurthy and P. Francis. On Heterogeneous Overlay Construction and Random Node Selection in Unstructured P2P Networks. In Proc. of INFOCOM, 2006.Google ScholarGoogle ScholarCross RefCross Ref
  31. W. Wang, C. Jin, and S. Jamin. Network Overlay Construction under Limited End-to-End Reachability. In Proc. of INFOCOM, 2005.Google ScholarGoogle ScholarCross RefCross Ref
  32. J. Widmer and M. Handley. Extending Equation-based Congestion Control to Multicast Applications. In Proc. of SIGCOMM, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Zattoo. http://www.zattoo.com.Google ScholarGoogle Scholar
  34. B. Zhang, W. Wang, S. Jamin, D. Massey, and L. Zhang. Universal IP multicast delivery. Computer Networks, 50(6):781--806, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. M. Zhang, Q. Zhang, L. Sun, and S. Yang. Understanding the Power of Pull-Based Streaming Protocol: Can We Do Better? JSAC, 25(9):1678--1694, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Heterogeneous gossip

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image Guide Proceedings
          Middleware '09: Proceedings of the 10th ACM/IFIP/USENIX International Conference on Middleware
          November 2009
          497 pages

          Publisher

          Springer-Verlag

          Berlin, Heidelberg

          Publication History

          • Published: 30 November 2009

          Qualifiers

          • research-article

          Acceptance Rates

          Overall Acceptance Rate203of948submissions,21%

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader