Advertisement

Practically-Self-stabilizing Vector Clocks in the Absence of Execution Fairness

  • Iosif SalemEmail author
  • Elad Michael Schiller
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11028)

Abstract

Vector clock algorithms are basic wait-free building blocks that facilitate causal ordering of events. As wait-free algorithms, they are guaranteed to complete their operations within a finite number of steps. Stabilizing algorithms allow the system to recover after the occurrence of transient faults, such as soft errors and arbitrary violations of the assumptions according to which the system was designed to behave.

We present the first, to the best of our knowledge, stabilizing vector clock algorithm for asynchronous crash-prone message-passing systems that can recover in a wait-free manner after the occurrence of transient faults (as well as communication and crash failures) in the absence of execution fairness. We use bounded message and storage sizes and do not rely on any means of synchronization.

The proposed algorithm provides bounded time recovery during fair executions that follow the last transient fault. The novelty is for the case of more challenging settings that consider no execution fairness. The proposed algorithm guarantees a bound on the number of times in which the system might violate safety (while existing algorithms might block forever due to the presence of both transient faults and crash failures).

References

  1. 1.
    Georgiou, C., Shvartsman, A.A.: Cooperative task-oriented computing: algorithms and complexity. Synth. Lect. Distrib. Comput. Theory 2(2), 1–167 (2011)CrossRefGoogle Scholar
  2. 2.
    Dijkstra, E.W.: Self-stabilizing systems in spite of distributed control. Commun. ACM 17(11), 643–644 (1974)CrossRefGoogle Scholar
  3. 3.
    Burns, J.E., Gouda, M.G., Miller, R.E.: Stabilization and pseudo-stabilization. Distrib. Comput. 7(1), 35–42 (1993)CrossRefGoogle Scholar
  4. 4.
    Alon, N., Attiya, H., Dolev, S., Dubois, S., Potop-Butucaru, M., Tixeuil, S.: Practically stabilizing SWMR atomic memory in message-passing systems. J. Comput. Syst. Sci. 81(4), 692–701 (2015)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Dolev, S., Kat, R.I., Schiller, E.M.: When consensus meets self-stabilization. J. Comput. Syst. Sci. 76(8), 884–900 (2010)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Blanchard, P., Dolev, S., Beauquier, J., Delaët, S.: Practically self-stabilizing paxos replicated state-machine. In: Noubir, G., Raynal, M. (eds.) NETYS 2014. LNCS, vol. 8593, pp. 99–121. Springer, Cham (2014).  https://doi.org/10.1007/978-3-319-09581-3_8CrossRefGoogle Scholar
  7. 7.
    Dolev, S., Georgiou, C., Marcoullis, I., Schiller, E.M.: Practically stabilizing virtual synchrony. In: Stabilization, Safety, and Security of Distributed Systems, SSS (2015)Google Scholar
  8. 8.
    Arora, A., Kulkarni, S.S., Demirbas, M.: Resettable vector clocks. J. Parallel Distrib. Comput. 66(2), 221–237 (2006)CrossRefGoogle Scholar
  9. 9.
    Tanenbaum, A.S., Van Steen, M.: Distributed Systems: Principles and Paradigms. Prentice-Hall, Upper Saddle River (2007)zbMATHGoogle Scholar
  10. 10.
    Almeida, J.B., Almeida, P.S., Baquero, C.: Bounded version vectors. In: Guerraoui, R. (ed.) DISC 2004. LNCS, vol. 3274, pp. 102–116. Springer, Heidelberg (2004).  https://doi.org/10.1007/978-3-540-30186-8_8CrossRefGoogle Scholar
  11. 11.
    Malkhi, D., Terry, D.B.: Concise version vectors in WinFS. Distrib. Comput. 20(3), 209–219 (2007)CrossRefGoogle Scholar
  12. 12.
    Bonomi, S., Dolev, S., Potop-Butucaru, M., Raynal, M.: Stabilizing server-based storage in Byzantine asynchronous message-passing systems. In: Symposium on Principles of. Distributed Computing, PODC, pp. 471–479. ACM(2015)Google Scholar
  13. 13.
    Salem, I., Schiller, E.M.: Practically-self-stabilizing vector clocks in the absence of execution fairness. CoRR abs/1712.08205 (2017)Google Scholar
  14. 14.
    Dolev, S., Dubois, S., Potop-Butucaru, M., Tixeuil, S.: Stabilizing data-link over non-FIFO channels with optimal fault-resilience. Inf. Process. Lett. 111(18), 912–920 (2011)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Dolev, S., Hanemann, A., Schiller, E.M., Sharma, S.: Self-stabilizing End-to-end communication in (bounded capacity, omitting, duplicating and non-FIFO) dynamic networks. In: Richa, A.W., Scheideler, C. (eds.) SSS 2012. LNCS, vol. 7596, pp. 133–147. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-33536-5_14CrossRefGoogle Scholar
  16. 16.
    Dolev, S.: Self-Stabilization. MIT Press, Cambridge (2000)zbMATHGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Chalmers University of TechnologyGothenburgSweden

Personalised recommendations