Peer-to-Peer Networking and Applications

, Volume 5, Issue 1, pp 74–91 | Cite as

Pulp: An adaptive gossip-based dissemination protocol for multi-source message streams

  • Pascal Felber
  • Anne-Marie Kermarrec
  • Lorenzo Leonini
  • Etienne Rivière
  • Spyros Voulgaris
Article

Abstract

Gossip-based protocols provide a simple, scalable, and robust way to disseminate messages in large-scale systems. In such protocols, messages are spread in an epidemic manner. Gossiping may take place between nodes using push, pull, or a combination. Push-based systems achieve reasonable latency and high resilience to failures but may impose an unnecessarily large redundancy and overhead on the system. At the other extreme, pull-based protocols impose a lower overhead on the network at the price of increased latencies. A few hybrid approaches have been proposed—typically pushing control messages and pulling data—to avoid the redundancy of high-volume content and single-source streams. Yet, to the best of our knowledge, no other system intermingles push and pull in a multiple-senders scenario, in such a way that data messages of one help in carrying control messages of the other and in adaptively adjusting its rate of operation, further reducing overall cost and improving both on delays and robustness. In this paper, we propose an efficient generic push-pull dissemination protocol, Pulp, which combines the best of both worlds. Pulp exploits the efficiency of push approaches, while limiting redundant messages and therefore imposing a low overhead, as pull protocols do. Pulp leverages the dissemination of multiple messages from diverse sources: by exploiting the push phase of messages to transmit information about other disseminations, Pulp enables an efficient pulling of other messages, which themselves help in turn with the dissemination of pending messages. We deployed Pulp on a cluster and on PlanetLab. Our results demonstrate that Pulp achieves an appealing trade-off between coverage, message redundancy, and propagation delay.

Keywords

Peer-to-Peer network Gossip-based dissemination Epidemic algorithm 

References

  1. 1.
    Bhagwan R, Savage S, Voelker GM (2003) Understanding availability. In: Proceedings of the 2nd International Workshop on Peer-to-Peer Systems (IPTPS’03). Berkeley, CA, pp 256–267Google Scholar
  2. 2.
    Birman KP, Hayden M, Ozkasap O, Xiao Z, Budiu M, Minsky Y (1999) Bimodal multicast. ACM Trans Comput Syst 17(2):41–88CrossRefGoogle Scholar
  3. 3.
    Bonald T, Massoulié L, Mathieu F, Perino D, Twigg A (2008) Epidemic live streaming: optimal performance trade-offs. In: SIGMETRICS. Annapolis, MA, pp 325–336Google Scholar
  4. 4.
    Champel M-L, Kermarrec A-M, Le Scouarnec N (2009) Fog: fighting the achilles’ heel of gossip protocols with fountain codes. In: SSS. Lyon, France, pp 180–194Google Scholar
  5. 5.
    Lo Cigno R, Russo A, Carra D (2008) On some fundamental properties of P2P push/pull protocols. In: Proceedings of the 2nd International Conference on Communications and Electronic (HUT-ICCE). HoiAn, Vietnam, pp 67–73CrossRefGoogle Scholar
  6. 6.
    Cohen B (2003) Incentives build robustness in bittorrent. In: Proceedings of the 1st workshop on economics of Peer-to-Peer systems. Berkeley, CAGoogle Scholar
  7. 7.
    Demers A, Greene D, Hauser C, Irish W, Larson J, Shenker S, Sturgis H, Swinehart D, Terry D (1987) Epidemic algorithms for replicated database maintenance. In: Proceedings of the 6th annual ACM symposium on Principles of Distributed Computing (PODC’87). Vancouver, Canada, pp 1–12Google Scholar
  8. 8.
    Eugster P, Handurukande S, Guerraoui R, Kermarrec A-M, Kouznetsov P (2003) Lightweight probabilistic broadcast. ACM Trans Comput Syst 21(4):341–374CrossRefGoogle Scholar
  9. 9.
    Frey D, Guerraoui R, Kermarrec A-M, Mogensen M, Monod M, Quéma V (2008) Gossiping capabilities. Technical Report LPD-REPORT-2008-010, EPFLGoogle Scholar
  10. 10.
    Ganesh AJ, Kermarrec A-M, Massoulié L (2003) Peer-to-Peer membership management for gossip-based protocols. IEEE Trans Comput 52(2):139–149CrossRefGoogle Scholar
  11. 11.
    Jelasity M, Voulgaris S, Guerraoui R, Kermarrec A-M, van Steen M (2007) Gossip-based peer sampling. ACM Trans Comput Syst 25(3). http://dl.acm.org/citation.cfm?id=1275520
  12. 12.
    Karp R, Schindelhauer C, Shenker S, Vocking B (2000) Randomized rumour spreading. In: IEEE proc 41st ann symp Foundations of Computer Science (FOCS), p 565Google Scholar
  13. 13.
    Kashyap S, Deb S, Naidu, KVM, Rastogi R, Srinivasan A (2006) Efficient gossip-based aggregate computation. In: PODS ’06: proceedings of the 25th ACM SIGMOD-SIGACT-SIGART symposium on principles of database systems. ACM Press, New York, pp 308–317CrossRefGoogle Scholar
  14. 14.
    Kermarrec A-M, Massoulié L, Ganesh AJ (2003) Probabilistic reliable dissemination in large-scale systems. IEEE Trans Parallel Distrib Syst 14(3):139–149CrossRefGoogle Scholar
  15. 15.
    Kermarrec A-M, Pace A, Quema V, Schiavoni V (2009) Nat-resilient gossip peer sampling. In: ICDCS ’09: proceedings of the 2009 29th IEEE international conference on distributed computing systems. IEEE Computer Society, Washington, pp 360–367CrossRefGoogle Scholar
  16. 16.
    Kermarrec A-M, van Steen M (2007) Gossiping in distributed systems. ACM Oper Syst Rev 41(5):2–7CrossRefGoogle Scholar
  17. 17.
    Kostoulas D, Psaltoulis D, Gupta I, Birman KP, Demers AJ (2007) Active and passive techniques for group size estimation in large-scale and dynamic distributed systems. J Syst Softw 80(10):1639–1658CrossRefGoogle Scholar
  18. 18.
    Li B, Qu Y, Keung GY, Xie S, Lin C, Liu J, Zhang X (2008) Inside the new coolstreaming: principles, measurements and performance implications. In: Proceedings of the 27th conference on computer communications (IEEE INFOCOM), pp 1031–1039Google Scholar
  19. 19.
    Li HC, Clement A, Marchetti M, Kapritsos M, Robison L, Alvisi L, Dahlin M (2008) Flightpath: obedience vs choice in cooperative services. In: Proceedings of the 8th USENIX symposium on Operating Systems Design and Implementation (OSDI ’08)Google Scholar
  20. 20.
    Li HC, Clement A, Wong EL, Napper J, Alvisi L, Dahlin M (2006) BAR gossip. In: Proc of 7th symposium on Operating System Design and Implementation (OSDI ’06), pp 191–2004Google Scholar
  21. 21.
    Leonini L, Rivière E, Felber P (2009) SPLAY: distributed systems evaluation made simple (or how to turn ideas into live systems in a breeze). In: NSDI’09: proceedings of the 6th symposium on networked systems design and implementation. USENIX, pp 185–198Google Scholar
  22. 22.
    Lin M, Marzullo K (1999) Directional gossip: gossip in a wide area network. Technical Report CS1999-0622, University of California, San DiegoGoogle Scholar
  23. 23.
    Lin M, Marzullo K, Masini S (2000) Gossip versus deterministic flooding: low-message overhead and high-reliability for broadcasting on small networks. In: Intl symposium on Distributed Computing (DISC 2000). Toledo, Spain, pp 85–89Google Scholar
  24. 24.
    Liu X, Lan J, Shenoy P, Ramaritham K (2006) Consistency maintenance in dynamic Peer-to-Peer overlay networks. Comput Networks 50(6):859–876CrossRefGoogle Scholar
  25. 25.
    Locher T, Meier R, Schmid S, Wattenhofer R (2007) Push-to-pull Peer-to-Peer live streaming. In: Proceedings of DISC 2007: 21st international symposium on Distributed Computing. Lemosos, CyprusGoogle Scholar
  26. 26.
    Pai V, Kumar K, Tamilmani K, Sambamurthy V, Mohr AE (2005) Chainsaw: eliminating trees from overlay multicast. In: IPTPS’05: the 4th international workshop on Peer-to-Peer systems, pp 127–140Google Scholar
  27. 27.
    Picconi F, Massoulié L (2008) Is there a future for mesh-based live video streaming? In: Proceedings of the 8th international conference on Peer-to-Peer computing (P2P’08). Aachen, GermanyGoogle Scholar
  28. 28.
    Russo A, Lo Cigno R (2010) Delay-aware push/pull protocols for live video streaming in P2P systems. In: Proceedings of the IEEE International Conference on Communications (ICC)Google Scholar
  29. 29.
    Sanghavi S, Hajek B, Massoulié L (2007) Gossiping with multiple messages. In: Proceedings of the 29th conference on computer communications (IEEE INFOCOM), pp 2135–2143Google Scholar
  30. 30.
    Srinivasan R, Liang C, Ramamritham K (1998) Maintaining temporal coherency of virtual data warehouses. In: RTSS ’98: proceedings of the IEEE real-time systems symposium. IEEE Computer Society, Washington, DC, p 60Google Scholar
  31. 31.
    Urgaonkar B, Ninan AG, Raunak MS, Shenoy P, Ramamritham K (2001) Maintaining mutual consistency for cached web objects. In: ICDCS ’01: proceedings of the the 21st international conference on distributed computing systems. IEEE Computer Society, Washington, DC, pp 371–380CrossRefGoogle Scholar
  32. 32.
    van Renesse R, Minsky Y, Hayden M (1998) A gossip-style failure detection service. In: IFIP (ed) Proc of Middleware, the IFIP international conference on distributed systems platforms and open distributed processing. The Lake District, UK, pp 55–70Google Scholar
  33. 33.
    Voulgaris S, Gavidia D, van Steen M (2005) CYCLON: inexpensive membership management for unstructured P2P overlays. J Netw Syst Manag 13(2):197–217CrossRefGoogle Scholar
  34. 34.
    Zhang X, Liu J, Li B, Yum T-SP (2005) Coolstreaming/DONet: a data-driven overlay network for efficient live media streaming. In: Proceedings of the 24th conference on computer communications (IEEE INFOCOM), pp 2102–2111Google Scholar

Copyright information

© Springer Science + Business Media, LLC 2011

Authors and Affiliations

  • Pascal Felber
    • 1
  • Anne-Marie Kermarrec
    • 2
  • Lorenzo Leonini
    • 1
  • Etienne Rivière
    • 1
  • Spyros Voulgaris
    • 3
  1. 1.Institut d’InformatiqueUniversité de NeuchâtelNeuchâtelSwitzerland
  2. 2.INRIA Rennes-Bretagne AtlantiqueRennes CedexFrance
  3. 3.Computer Science DepartmentVrije UniversiteitAmsterdamThe Netherlands

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