Consistency in Scalable Systems

  • M. I. Ruiz-Fuertes
  • M. R. Pallardó-Lozoya
  • F. D. Muñoz-Escoí
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7566)


While eventual consistency is the general consistency guarantee ensured in cloud environments, stronger guarantees are in fact achievable. We show how scalable and highly available systems can provide processor, causal, sequential and session consistency during normal functioning. Failures and network partitions negatively affect consistency and generate divergence. After the failure or the partition, reconciliation techniques allow the system to restore consistency.


DSM Consistency Scalability Cloud Systems Data Centers Distributed Systems 


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  1. 1.
    Ahamad, M., Bazzi, R.A., John, R., Kohli, P., Neiger, G.: The power of processor consistency. In: Proceedings of the Fifth Annual ACM Symposium on Parallel Algorithms and Architectures, SPAA 1993, pp. 251–260. ACM, New York (1993), CrossRefGoogle Scholar
  2. 2.
    Alvarez, A., Arévalo, S., Cholvi, V., Fernández, A., Jiménez, E.: On the Interconnection of Message Passing Systems. Inf. Process. Lett. 105(6), 249–254 (2008)zbMATHCrossRefGoogle Scholar
  3. 3.
    Amazon Web Services LLC: Amazon Simple Storage Service (S3). Website (March 2011),
  4. 4.
    Baker, J., Bond, C., Corbett, J.C., Furman, J.J., Khorlin, A., Larson, J., Léon, J., Li, Y., Lloyd, A., Yushprakh, V.: Megastore: Providing Scalable, Highly Available Storage for interactive services. In: 5th Biennial Conf. on Innovative Data Systems Research (CIDR), Asilomar, CA, USA, pp. 223–234 (January 2011)Google Scholar
  5. 5.
    Baldoni, R., Beraldi, R., Friedman, R., van Renesse, R.: The Hierarchical Daisy Architecture for Causal Delivery. Distributed Systems Engineering 6(2), 71–81 (1999)CrossRefGoogle Scholar
  6. 6.
    Bernstein, P.A., Hadzilacos, V., Goodman, N.: Concurrency Control and Recovery in Database Systems. Addison-Wesley (1987)Google Scholar
  7. 7.
    Bernstein, P.A., Reid, C.W., Das, S.: Hyder - A Transactional Record Manager for Shared Flash. In: 5th Biennial Conf. on Innovative Data Systems Research (CIDR), Asilomar, CA, USA, pp. 9–20 (January 2011)Google Scholar
  8. 8.
    Bershad, B.N., Zekauskas, M.J., Sawdon, W.A.: The Midway Distributed Shared Memory System. In: Proc. IEEE CompCon Conf. (1993)Google Scholar
  9. 9.
    Brewer, E.A.: Towards Robust Distributed Systems (Abstract). In: Proc. ACM Symp. Princ. Distrib. Comput., p. 7 (2000)Google Scholar
  10. 10.
    Budhiraja, N., Marzullo, K., Schneider, F.B., Toueg, S.: The Primary-Backup Approach. In: Mullender, S.J. (ed.) Distributed Systems, 2nd edn., ch. 8, pp. 199–216. Addison-Wesley, ACM Press (1993)Google Scholar
  11. 11.
    Campbell, D.G., Kakivaya, G., Ellis, N.: Extreme Scale with Full SQL Language Support in Microsoft SQL Azure. In: Intnl. Conf. on Mngmnt. of Data (SIGMOD), pp. 1021–1024. ACM, New York (2010), Google Scholar
  12. 12.
    Cholvi, V., Jiménez, E., Anta, A.F.: Interconnection of distributed memory models. J. Parallel Distrib. Comput. 69(3), 295–306 (2009)CrossRefGoogle Scholar
  13. 13.
    Cooper, B.F., Ramakrishnan, R., Srivastava, U., Silberstein, A., Bohannon, P., Jacobsen, H., Puz, N., Weaver, D., Yerneni, R.: PNUTS: Yahoo!’s hosted data serving platform. PVLDB 1(2), 1277–1288 (2008)Google Scholar
  14. 14.
    Daudjee, K., Salem, K.: Lazy Database Replication with Ordering Guarantees. In: Proc. Int. Conf. Data Eng., pp. 424–435. IEEE-CS (2004)Google Scholar
  15. 15.
    Daudjee, K., Salem, K.: Lazy Database Replication with Snapshot Isolation. In: Proc. Int. Conf. Very Large Data Bases, pp. 715–726. ACM (2006)Google Scholar
  16. 16.
    DeCandia, G., Hastorun, D., Jampani, M., Kakulapati, G., Lakshman, A., Pilchin, A., Sivasubramanian, S., Vosshall, P., Vogels, W.: Dynamo: Amazon’s Highly Available Key-value Store. In: ACM Symp. Oper. Syst. Princ., pp. 205–220 (2007)Google Scholar
  17. 17.
    Fernández, A., Jiménez, E., Cholvi, V.: On the interconnection of causal memory systems. J. Parallel Distrib. Comput. 64(4), 498–506 (2004)zbMATHCrossRefGoogle Scholar
  18. 18.
    Gilbert, S., Lynch, N.A.: Brewer’s Conjecture and the Feasibility of Consistent, Available, Partition-Tolerant Web Services. ACM SIGACT News 33(2), 51–59 (2002)CrossRefGoogle Scholar
  19. 19.
    Goodman, J.R.: Cache Consistency and Sequential Consistency. Tech. Rep. 61, SCI Committee (March 1989)Google Scholar
  20. 20.
    Gray, J., Helland, P., O’Neil, P.E., Shasha, D.: The Dangers of Replication and a Solution. In: Proc. ACM SIGMOD Int. Conf. Manage. Data, pp. 173–182. ACM (1996)Google Scholar
  21. 21.
    Helland, P., Campbell, D.: Building on Quicksand. In: Proc. Bienn. Conf. Innov. Data Syst. Research (2009),
  22. 22.
    Hutto, P., Ahamad, M.: Slow Memory: Weakening Consistency to Enhance Concurrency in Distributed Shared Memories. In: Proceedings of the 10th International Conference on Distributed Computing Systems, pp. 302–311 (May 1990)Google Scholar
  23. 23.
    Johnson, S., Jahanian, F., Shah, J.: The Inter-group Router Approach to Scalable Group Composition. In: ICDCS, pp. 4–14 (1999)Google Scholar
  24. 24.
    Kraska, T., Hentschel, M., Alonso, G., Kossmann, D.: Consistency Rationing in the Cloud: Pay only when it matters. PVLDB 2(1), 253–264 (2009)Google Scholar
  25. 25.
    Lamport, L.: How to Make a Multiprocessor Computer that Correctly Executes multiprocess programs. IEEE Trans. Computers 28(9), 690–691 (1979)zbMATHCrossRefGoogle Scholar
  26. 26.
    Lipton, R.J., Sandberg, J.S.: Pram: A Scalable Shared Memory. Tech. Rep. CS-TR-180-88, Princeton University, Department of Computer Science (September 1988)Google Scholar
  27. 27.
    Mosberger, D.: Memory Consistency Models. Operating Systems Review 27(1), 18–26 (1993)CrossRefGoogle Scholar
  28. 28.
    Ruiz-Fuertes, M.I., Muñoz-Escoí, F.D.: Refinement of the One-Copy Serializable Correctness Criterion. Tech. Rep. ITI-SIDI-2011/004, Instituto Tecnológico de Informática, Valencia, Spain (November 2011)Google Scholar
  29. 29.
    Stonebraker, M., Madden, S., Abadi, D.J., Harizopoulos, S., Hachem, N., Helland, P.: The End of an Architectural Era (It’s Time for a Complete Rewrite). In: 33rd Intnl. Conf. on Very Large Data Bases (VLDB), pp. 1150–1160. ACM Press, Vienna (2007)Google Scholar
  30. 30.
    Terry, D.B., Demers, A.J., Petersen, K., Spreitzer, M., Theimer, M., Welch, B.B.: Session Guarantees for Weakly Consistent Replicated Data. In: Proc. Int. Conf. Parallel Distrib. Inform. Syst., pp. 140–149. IEEE-CS (1994)Google Scholar
  31. 31.
    Vogels, W.: Eventually Consistent. Communications of the ACM (CACM) 52(1), 40–44 (2009)CrossRefGoogle Scholar
  32. 32.
    VoltDB, Inc.: VoltDB technical overview: A high performance, scalable RDBMS for Big Data, high velocity OLTP and realtime analytics. Website (April 2012),
  33. 33.
    Wiesmann, M., Schiper, A.: Comparison of Database Replication Techniques Based on Total Order Broadcast. IEEE T. Knowl. Data En. 17(4), 551–566 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • M. I. Ruiz-Fuertes
    • 1
  • M. R. Pallardó-Lozoya
    • 1
  • F. D. Muñoz-Escoí
    • 1
  1. 1.Instituto Universitario Mixto Tecnolóogico de InformáticaUniversidad Politécnica de ValenciaValenciaSpain

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