Reliable Communication Infrastructure for Adaptive Data Replication

  • Mouna Allani
  • Benoît Garbinato
  • Amirhossein Malekpour
  • Fernando Pedone
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5870)

Abstract

In this paper, we propose a data replication algorithm adaptive to unreliable environments. The data replication algorithm, named Adaptive Data Replication (ADR), has already an adaptiveness mechanism encapsulated in its dynamic replica placement strategy. Our extension of ADR to unreliable environments provides a data replication solution that is adaptive both in terms of replica placement and in terms of request routing. At the routing level, this solution takes the unreliability of the environment into account, in order to maximize reliable delivery of requests. At the replica placement level, the dynamically changing origin and frequency of read/write requests are analyzed, in order to define a set of replica that minimizes communication cost. Performance evaluation shows that this original combination of two adaptive strategies makes it possible to ensure high request delivery, while minimizing communication overhead in the system.

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References

  1. 1.
    Amir, Y., Tutu, C.: From total order to database replication. In: Proceedings of ICDCS, pp. 494–503. IEEE, Los Alamitos (2002)Google Scholar
  2. 2.
    Bernstein, P.A., Goodman, N., Wong, E., Reeve, C.L., Rothnie Jr., J.B.: Query processing in a system for distributed databases (sdd-1). ACM Trans. Database Syst. 6(4) (1981)Google Scholar
  3. 3.
    Elnikety, S., Dropsho, S.G., Zwaenepoel, W.: Tashkent+: memory-aware load balancing and update filtering in replicated databases. In: Euro. Sys., pp. 399–412 (2007)Google Scholar
  4. 4.
    Garbinato, B., Pedone, F., Schmidt, R.: An adaptive algorithm for efficient message diffusion in unreliable environments. In: Proceedings of IEEE DSN (2004)Google Scholar
  5. 5.
    Holliday, J., Agrawal, D., El Abbadi, A.: The performance of database replication with group multicast. In: Proceedings of FTCS, pp. 158–165. IEEE Computer Society Press, Los Alamitos (1999)Google Scholar
  6. 6.
    Jannotti, J., Gifford, D.K., Johnson, K.L., Kaashoek, M.F., O’Toole Jr., J.W.: Overcast: Reliable multicasting with an overlay network. In: Proceedings of OSDI (October 2000)Google Scholar
  7. 7.
    Kalpakis, K., Dasgupta, K., Wolfson, O.: Optimal placement of replicas in trees with read, write, and storage costs. IEEE Trans. Parallel Distrib. Syst. 12(6) (2001)Google Scholar
  8. 8.
    Kemme, B., Bartoli, A., Babaoglu, Ö.: Online reconfiguration in replicated databases based on group communication. In: DSN, pp. 117–130 (2001)Google Scholar
  9. 9.
    Kostic, D., Rodriguez, A., Albrecht, J., Bhirud, A., Vahdat, A.: Using random subsets to build scalable network services. In: Proceedings of USITS (March 2003)Google Scholar
  10. 10.
    MacCormick, J., Murphy, N., Ramasubramanian, V., Wieder, U., Yang, J., Zhou, L.: Kinesis: A new approach to replica placement in distributed storage systems. ACM Transactions on Storage (TOS) (to appear)Google Scholar
  11. 11.
    Rabinovich, M., Rabinovich, I., Rajaraman, R., Aggarwal, A.: A dynamic object replication and migration protocol for an internet hosting service. In: ICDCS (1999)Google Scholar
  12. 12.
    Serrano, D., no-Martínez, M., Jiménez-Peris, P.R., Kemme, B.: An autonomic approach for replication of internet-based services. In: SRDS, Washington, DC, USA, pp. 127–136. IEEE Computer Society, Los Alamitos (2008)Google Scholar
  13. 13.
    Serrano, D., Patiño-Martínez, M., Jiménez-Peris, R., Kemme, B.: Boosting database replication scalability through partial replication and 1-copy-snapshot-isolation. In: PRDC, pp. 290–297 (2007)Google Scholar
  14. 14.
    Sivasubramanian, S., Alonso, G., Pierre, G., van Steen, M.: GlobeDB: Autonomic data replication for web applications. In: Proc. of the 14th International World-Wide Web Conference, Chiba, Japan, pp. 33–42 (May 2005)Google Scholar
  15. 15.
    Stonebraker, M.: The design and implementation of distributed ingres. In: The INGRES Papers (1986)Google Scholar
  16. 16.
    Tsoumakos, D., Roussopoulos, N.: An adaptive probabilistic replication method for unstructured p2p networks. In: OTM Conferences, vol. (1) (2006)Google Scholar
  17. 17.
    van Renesse, R., Birman, K.P., Hayden, M., Vaysburd, A., Karr, D.A.: Building adaptive systems using ensemble. Softw., Pract. Exper. 28(9) (1998)Google Scholar
  18. 18.
    Vaysburd, A., Birman, K.P.: The maestro approach to building reliable interoperable distributed applications with multiple execution styles. TAPOS 4(2) (1998)Google Scholar
  19. 19.
    Wolfson, O., Jajodia, S., Huang, Y.: An adaptive data replication algorithm. ACM Trans. Database Syst. 22(2) (1997)Google Scholar
  20. 20.
    Wolfson, O., Milo, A.: The multicast policy and its relationship to replicated data placement. ACM Trans. Database Syst. 16(1) (1991)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Mouna Allani
    • 1
  • Benoît Garbinato
    • 1
  • Amirhossein Malekpour
    • 2
  • Fernando Pedone
    • 2
  1. 1.University of Lausanne 
  2. 2.University of Lugano 

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