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Efficient Hierarchical Quorums in Unstructured Peer-to-Peer Networks

  • Kevin Henry
  • Colleen Swanson
  • Qi Xie
  • Khuzaima Daudjee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5870)

Abstract

Managing updates in a peer-to-peer (P2P) network can be a challenging task, especially in the unstructured setting. If one peer reads or updates a data item, then it is desirable to read the most recent version or to have the update visible to all other peers. In practice, this should be accomplished by coordinating and writing to only a small number of peers. We propose two approaches, inspired by hierarchical quorums, to solve this problem in unstructured P2P networks. Our first proposal provides uniform load balancing, while the second sacrifices full load balancing for larger average quorum intersection, and hence greater tolerance to network churn. We demonstrate that applying a random logical tree structure to peers on a per-data item basis allows us to achieve near optimal quorum size, thus minimizing the number of peers that must be coordinated to perform a read or write operation. Unlike previous approaches, our random hierarchical quorums are always guaranteed to overlap at at least one peer when all peers are reachable and, as demonstrated through performance studies, prove to be more resilient to changing network conditions to maximize quorum intersection than previous approaches with a similar quorum size. Furthermore, our two quorum approaches are interchangeable within the same network, providing adaptivity by allowing one to be swapped for the other as network conditions change.

Keywords

Data Item Replication Rate Quorum System Federal Information Processing Standard Change Network Condition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
  2. 2.
    Liang, J., Kumar, R., Ross, K.W.: The fasttrack overlay: a measurement study. Comput. Netw. 50(6), 842–858 (2006)CrossRefGoogle Scholar
  3. 3.
    Del Vecchio, D., Son, S.H.: Flexible update management in peer-to-peer database systems. In: IDEAS 2005: Proceedings of the 9th International Database Engineering & Application Symposium, Washington, DC, USA, pp. 435–444. IEEE Computer Society Press, Los Alamitos (2005)Google Scholar
  4. 4.
    Kumar, A.: Hierarchical quorum consensus: A new algorithm for managing replicated data. IEEE Trans. Comput. 40(9), 996–1004 (1991)CrossRefGoogle Scholar
  5. 5.
    National Institute of Standards and Technology. FIPS 180-2, secure hash standard, federal information processing standard (FIPS), publication 180-2. Technical report, Department of Commerce (August 2002)Google Scholar
  6. 6.
    Joseph, S.: Neurogrid simulation setup, http://www.neurogrid.net/php/simulation.php
  7. 7.
    Kirk, P.: Gnutella protocol development: Standard message architecture, http://rfc-gnutella.sourceforge.net/developer/testing/message-Architecture.html
  8. 8.
    Kostoulas, D., Psaltoulis, D., Gupta, I., Birman, K.P., Demers, A.J.: Active and passive techniques for group size estimation in large-scale and dynamic distributed systems. J. Syst. Softw. 80(10), 1639–1658 (2007)CrossRefGoogle Scholar
  9. 9.
    Gifford, D.K.: Weighted voting for replicated data. In: SOSP 1979: Proceedings of the seventh ACM symposium on Operating systems principles, pp. 150–162. ACM, New York (1979)CrossRefGoogle Scholar
  10. 10.
    Cheung, S.Y., Ammar, M.H., Ahamad, M.: The grid protocol: A high performance scheme for maintaining replicated data. IEEE Trans. on Knowl. and Data Eng. 4(6), 582–592 (1992)CrossRefGoogle Scholar
  11. 11.
    Naor, M., Wool, A.: The load, capacity, and availability of quorum systems. SIAM J. Comput. 27(2), 423–447 (1998)zbMATHCrossRefMathSciNetGoogle Scholar
  12. 12.
    Kumar, A., Rabinovich, M., Sinha, R.K.: A performance study of general grid structures for replicated data. In: Proceedings the 13th International Conference on Distributed Computing Systems, May 1993, pp. 178–185 (1993)Google Scholar
  13. 13.
    Agrawal, D., El Abbadi, A.: The tree quorum protocol: an efficient approach for managing replicated data. In: Proceedings of the Sixteenth International Conference on Very Large Databases, pp. 243–254. Morgan Kaufmann Publishers Inc., San Francisco (1990)Google Scholar
  14. 14.
    Jiménez-Peris, R., Patino-Martínez, M., Alonso, G., Kemme, B.: Are quorums an alternative for data replication? ACM Trans. Database Syst. 28(3), 257–294 (2003)CrossRefGoogle Scholar
  15. 15.
    Wool, A.: Quorum systems in replicated databases: science or fiction. Bull. IEEE Technical Committee on Data Engineering 21, 3–11 (1998)Google Scholar
  16. 16.
    Freisleben, B., Koch, H.-H., Theel, O.: Designing multi-level quorum schemes for highly replicated data. In: Proc. of the 1991 Pacific Rim International Symposium on Fault Tolerant Systems, pp. 154–159. IEEE Computer Society Press, Los Alamitos (1990)Google Scholar
  17. 17.
    Freisleben, B., Koch, H.-H., Theel, O.: The electoral district strategy for replicated data in distributed systems. In: Proc. of the 5th Intern. Conference of Fault-Tolerant Computing Systems, pp. 100–111 (1991)Google Scholar
  18. 18.
    Baldoni, R., Jiménez-Peris, R., Patino-Martínez, M., Querzoni, L., Virgillito, A.: Dynamic quorums for DHT-based enterprise infrastructures. J. Parallel Distrib. Comput. 68(9), 1235–1249 (2008)CrossRefGoogle Scholar
  19. 19.
    Brunskill, E.: Building peer-to-peer systems with chord, a distributed lookup service. In: HOTOS 2001: Proceedings of the Eighth Workshop on Hot Topics in Operating Systems, Washington, DC, USA, p. 81. IEEE Computer Society, Los Alamitos (2001)Google Scholar
  20. 20.
    Zhang, Z.: The power of DHT as a logical space. In: IEEE International Workshop on Future Trends of Distributed Computing Systems, pp. 325–331 (2004)Google Scholar
  21. 21.
    Lin, S., Lian, Q., Zang, Z.: A practical distributed mutual exclusion protocol in dynamic peer-to-peer systems. In: Voelker, G.M., Shenker, S. (eds.) IPTPS 2004. LNCS, vol. 3279, pp. 11–21. Springer, Heidelberg (2005)Google Scholar
  22. 22.
    Naor, M., Wieder, U.: Scalable and dynamic quorum systems. Distrib. Comput. 17(4), 311–322 (2005)CrossRefGoogle Scholar
  23. 23.
    Silaghi, B., Keleher, P., Bhattacharjee, B.: Multi-dimensional quorum sets for read-few write-many replica control protocols. In: Fourth International Workshop on Global and Peer-to-Peer Computing (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Kevin Henry
    • 1
  • Colleen Swanson
    • 1
  • Qi Xie
    • 1
  • Khuzaima Daudjee
    • 1
  1. 1.David R. Cheriton School of Computer ScienceUniversity of WaterlooWaterlooCanada

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