Does the Operational Model Capture Partition Tolerance in Distributed Systems?

  • Grégoire BoninEmail author
  • Achour Mostéfaoui
  • Matthieu Perrin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11657)


In large scale distributed systems, replication is essential in order to provide availability and partition tolerance. Such systems are abstracted by the wait-free model, composed of asynchronous processes that communicate by sending and receiving messages, and in which any process may crash. Complexity in local memory has already been studied for several objects, including sets, databases and collaborative editors. However, the literature has focused on a subclass of algorithms, operating in the so-called operational model, in which processes can only broadcast one message per update operation and the read operation incurs no communication.

This paper tackles the following question: are the operational model and the wait-free model equivalent from the complexity point of view? We show that, under a weak consistency criterion, implementations in the wait-free model require strictly less local memory than their counterparts in the operational model.


Operational model Eventual consistency Space complexity Update consistency Wait-free model 


  1. 1.
    Attiya, H., Burckhardt, S., Gotsman, A., Morrison, A., Yang, H., Zawirski, M.: Specification and complexity of collaborative text editing. In: Symposium on Principles of Distributed Computing, pp. 259–268. ACM (2016)Google Scholar
  2. 2.
    Attiya, H., Ellen, F., Morrison, A.: Limitations of highly-available eventually-consistent data stores. IEEE Trans. Parallel Distrib. Syst. 28(1), 141–155 (2017)CrossRefGoogle Scholar
  3. 3.
    Baldoni, R., Brzezinski, J., Hélary, J.M., Mostefaoui, A., Raynal, M.: Characterization of consistent global checkpoints in large-scale distributed systems. In: Workshop on Future Trends of Distributed Computing Systems, pp. 314–323. IEEE (1995)Google Scholar
  4. 4.
    Bonin, G., Achour, M., Perrin, M.: Does the operational model capture partition tolerance in distributed systems? extended version (2019)Google Scholar
  5. 5.
    Burckhardt, S., Gotsman, A., Yang, H., Zawirski, M.: Replicated data types: specification, verification, optimality. In: ACM Sigplan Notices, vol. 49, pp. 271–284. ACM (2014)Google Scholar
  6. 6.
    Gilbert, S., Lynch, N.: Brewer’s conjecture and the feasibility of consistent, available, partition-tolerant web services. ACM Sigact News 33, 51–59 (2002)CrossRefGoogle Scholar
  7. 7.
    Perrin, M.: Distributed Systems: Concurrency and Consistency. Elsevier, Amsterdam (2017)Google Scholar
  8. 8.
    Perrin, M., Mostefaoui, A., Jard, C.: Update consistency for wait-free concurrent objects. In: International Parallel and Distributed Processing Symposium, pp. 219–228. IEEE (2015)Google Scholar
  9. 9.
    Randell, B., Lee, P., Treleaven, P.C.: Reliability issues in computing system design. ACM Comput. Surv. (CSUR) 10(2), 123–165 (1978)CrossRefGoogle Scholar
  10. 10.
    Raynal, M., Schiper, A., Toueg, S.: The causal ordering abstraction and a simple way to implement it. Inf. Process. Lett. 39(6), 343–350 (1991)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Shapiro, M., Preguiça, N., Baquero, C., Zawirski, M.: Conflict-free replicated data types. In: Défago, X., Petit, F., Villain, V. (eds.) SSS 2011. LNCS, vol. 6976, pp. 386–400. Springer, Heidelberg (2011). Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Grégoire Bonin
    • 1
    Email author
  • Achour Mostéfaoui
    • 1
  • Matthieu Perrin
    • 1
  1. 1.LS2NUniversité de NantesNantesFrance

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