Dynamic Regular Registers in Systems with Churn

  • Andreas Klappenecker
  • Hyunyoung Lee
  • Jennifer L. Welch
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6976)


Distributed systems with churn, or dynamic distributed systems, allow the processes to join and leave the system at will. In this paper, we present a new consistency condition for shared read-write registers which is based on multi-writer regularity, but allows for the likelihood of the register to lose its state with some probability; we call this a dynamic regular register. We then describe an algorithm for implementing a dynamic regular register using copies of the register distributed among the processes. When a process joins the system, it attempts to obtain an up-to-date copy of the data from other processes. Copies of the register are updated by broadcasting information. To model the dynamicity of the system with churn, we use a continuous-time birth-death process which is a special case of continuous-time Markov processes. Then, we analyze the probability and the time duration that the dynamic regular register system keeps its state, given the joining rate and the leaving rate of the processes.


Dynamic Regular Register Dynamic Systems Churn Register Multi-Writer Regularity Markov Process 


  1. 1.
    Aguilera, M.K.: A pleasant stroll through the land of infinitely many creatures. SIGACT News Distributed Computing Column 35, 36–59 (2004)CrossRefGoogle Scholar
  2. 2.
    Anceaume, E., Défago, X., Potop-Butucaru, M., Roy, M.: A framework for proving the self-organization of dynamic systems. CoRR abs/1011.2312 (2010)Google Scholar
  3. 3.
    Baldoni, R., Bertier, M., Raynal, M., Tucci-Piergiovanni, S.: Looking for a definition of dynamic distributed systems. In: Malyshkin, V.E. (ed.) PaCT 2007. LNCS, vol. 4671, pp. 1–14. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  4. 4.
    Baldoni, R., Bonomi, S., Kermarrec, A.M., Raynal, M.: Implementing a register in a dynamic distributed system. In: The 29th IEEE International Conference on Distributed Computing Systems (ICDCS 2009), pp. 639–647 (2009)Google Scholar
  5. 5.
    Baldoni, R., Bonomi, S., Raynal, M.: Regular register: An implementation in a churn prone environment. In: Kutten, S., Žerovnik, J. (eds.) SIROCCO 2009. LNCS, vol. 5869, pp. 15–29. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  6. 6.
    Bhat, U.N.: An Introduction to Queuing Theory. Birkhäuser, Basel (2008)CrossRefGoogle Scholar
  7. 7.
    Dolev, S., Gilbert, S., Lynch, N.A., Shvartsman, A.A., Welch, J.L.: GeoQuorums: Implementing atomic memory in mobile ad hoc networks. In: Fich, F.E. (ed.) DISC 2003. LNCS, vol. 2848, pp. 306–320. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  8. 8.
    Gafni, E., Koutsoupias, E.: On uniform protocols. Tech. rep. (1998), http://www.cs.ucla.edu/~eli/eli.html
  9. 9.
    Gilbert, S., Lynch, N.A., Shvartsman, A.A.: Rambo: A robust, reconfigurable atomic memory service for dynamic networks. Distributed Computing 23(4), 225–272 (2010)CrossRefMATHGoogle Scholar
  10. 10.
    Kijima, M.: Markov Processes for Stochastic Modeling. Chapman & Hall, Boca Raton (1997)CrossRefMATHGoogle Scholar
  11. 11.
    Ko, S.Y., Hoque, I., Gupta, I.: Using tractable and realistic churn models to analyze quiescence behavior of distributed protocols. In: IEEE Symposium on Reliable Distributed Systems (SRDS 2008), pp. 259–268 (2008)Google Scholar
  12. 12.
    Kuhn, F., Schmid, S., Smit, J., Wattenhofer, R.: A blueprint for constructing peer-to-peer systems robust to dynamic worst-case joins and leaves. In: 14th IEEE International Workshop on Quality of Service (IWQoS 2006), pp. 12–19 (2006)Google Scholar
  13. 13.
    Lamport, L.: On interprocess communication, Part I: Models, Part II: Algorithms. Distributed Computing 1(2), 77–101 (1986)CrossRefMATHGoogle Scholar
  14. 14.
    Leonard, D., Yao, Z., Rai, V., Loguinov, D.: On lifetime-based node failure and stochastic resilience of decentralized peer-to-peer networks. IEEE/ACM Trans. Netw. 15, 644–656 (2007)CrossRefGoogle Scholar
  15. 15.
    Lynch, N.A., Shvartsman, A.A.: Rambo: A reconfigurable atomic memory service for dynamic networks. In: Malkhi, D. (ed.) DISC 2002. LNCS, vol. 2508, pp. 173–190. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  16. 16.
    Merritt, M., Taubenfeld, G.: Computing with infinitely many processes under assumptions on concurrency and participation. In: Herlihy, M.P. (ed.) DISC 2000. LNCS, vol. 1914, pp. 164–178. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  17. 17.
    Neely, M.J., Golubchik, L.: Utility optimization for dynamic peer-to-peer networks with tit-for-tat constraints. In: 30th IEEE International Conference on Computer Communications, IEEE INFOCOM (2011)Google Scholar
  18. 18.
    Ross, S.M.: Introduction to Probability Models, 7th edn. Academic Press, London (2000)MATHGoogle Scholar
  19. 19.
    Roy, M., Bonnet, F., Querzoni, L., Bonomi, S., Killijian, M.O., Powell, D.: Geo-registers: An abstraction for spatial-based distributed computing. In: Baker, T.P., Bui, A., Tixeuil, S. (eds.) OPODIS 2008. LNCS, vol. 5401, pp. 534–537. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  20. 20.
    Shao, C., Welch, J.L., Pierce, E., Lee, H.: Multiwriter consistency conditions for shared memory registers. SIAM J. on Computing 40, 28–62 (2011)MathSciNetCrossRefMATHGoogle Scholar
  21. 21.
    Taylor, H.M., Karlin, S.: An Introduction to Stochastic Modeling, 3rd edn. Academic Press, London (1998)MATHGoogle Scholar
  22. 22.
    Wolf, R.W.: Stochastic Modeling and the Theory of Queues. Prentice-Hall, Englewood Cliffs (1989)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Andreas Klappenecker
    • 1
  • Hyunyoung Lee
    • 1
  • Jennifer L. Welch
    • 1
  1. 1.Department of Computer Science and EngineeringTexas A&M UniversityUSA

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