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Self-stabilizing Snapshot Objects for Asynchronous Failure-Prone Networked Systems

  • Chryssis Georgiou
  • Oskar Lundström
  • Elad Michael SchillerEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11704)

Abstract

A snapshot object simulates the behavior of an array of single-writer/multi-reader shared registers that can be read atomically. Delporte-Gallet et al. proposed two fault-tolerant algorithms for snapshot objects in asynchronous crash-prone message-passing systems. Their first algorithm is non-blocking; it allows snapshot operations to terminate once all write operations had ceased. It uses \(\mathcal {O}(n)\) messages of \(\mathcal {O}(n \cdot \nu )\) bits, where n is the number of nodes and \(\nu \) is the number of bits it takes to represent the object. Their second algorithm allows snapshot operations to always terminate independently of write operations. It incurs \(\mathcal {O}(n^2)\) messages. The fault model of Delporte-Gallet et al. considers node failures (crashes). We aim at the design of even more robust snapshot objects. We do so through the lenses of self-stabilization—a very strong notion of fault-tolerance. In addition to Delporte-Gallet et al. ’s fault model, a self-stabilizing algorithm can recover after the occurrence of transient faults; these faults represent arbitrary violations of the assumptions according to which the system was designed to operate (as long as the code stays intact). In particular, in this work, we propose self-stabilizing variations of Delporte-Gallet et al. ’s non-blocking algorithm and always-terminating algorithm. Our algorithms have similar communication costs to the ones by Delporte-Gallet et al. and \(\mathcal {O}(1)\) recovery time (in terms of asynchronous cycles) from transient faults. The main differences are that our proposal considers repeated gossiping of \(\mathcal {O}(\nu )\) bits messages and deals with bounded space, which is a prerequisite for self-stabilization.

References

  1. 1.
    Afek, Y., Attiya, H., Dolev, D., Gafni, E., Merritt, M., Shavit, N.: Atomic snapshots of shared memory. J. ACM 40(4), 873–890 (1993)CrossRefGoogle Scholar
  2. 2.
    Anderson, J.H.: Multi-writer composite registers. Distrib. Comput. 7(4), 175–195 (1994)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Dijkstra, E.W.: Self-stabilizing systems in spite of distributed control. Commun. ACM 17(11), 643–644 (1974)CrossRefGoogle Scholar
  4. 4.
    Dolev, S.: Self-Stabilization. MIT Press, Cambridge (2000)CrossRefGoogle Scholar
  5. 5.
    Attiya, H., Bar-Noy, A., Dolev, D.: Sharing memory robustly in message-passing systems. J. ACM 42(1), 124–142 (1995)CrossRefGoogle Scholar
  6. 6.
    Delporte-Gallet, C., Fauconnier, H., Rajsbaum, S., Raynal, M.: Implementing snapshot objects on top of crash-prone asynchronous message-passing systems. IEEE Trans. Parallel Distrib. Syst. 29(9), 2033–2045 (2018)CrossRefGoogle Scholar
  7. 7.
    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
  8. 8.
    Dolev, S., Petig, T., Schiller, E.M.: Self-stabilizing and private distributed shared atomic memory in seldomly fair message passing networks. CoRR abs/1806.03498 (2018)Google Scholar
  9. 9.
    Georgiou, C., Lundström, O., Schiller, E.M.: Self-stabilizing snapshot objects for asynchronous failure-prone networked systems. CoRR (2019)Google Scholar
  10. 10.
    Georgiou, C., Shvartsman, A.A.: Cooperative Task-Oriented Computing: Algorithms and Complexity. Synthesis Lectures on Distributed Computing Theory. Morgan & Claypool Publishers (2011)Google Scholar
  11. 11.
    Lynch, N.A.: Distributed Algorithms. Morgan Kaufmann, San Francisco (1996)zbMATHGoogle Scholar
  12. 12.
    Awerbuch, B., Patt-Shamir, B., Varghese, G., Dolev, S.: Self-stabilization by local checking and global reset. In: Tel, G., Vitányi, P. (eds.) WDAG 1994. LNCS, vol. 857, pp. 326–339. Springer, Heidelberg (1994).  https://doi.org/10.1007/BFb0020443CrossRefGoogle Scholar
  13. 13.
    Imbs, D., Mostéfaoui, A., Perrin, M., Raynal, M.: Set-constrained delivery broadcast: Definition, abstraction power, and computability limits. In: 19th Distributed Computing and Networking, ICDCN, ACM (2018) 7:1–7:10Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Chryssis Georgiou
    • 1
  • Oskar Lundström
    • 2
  • Elad Michael Schiller
    • 2
    Email author
  1. 1.Computer ScienceUniversity of CyprusNicosiaCyprus
  2. 2.Computer Science and EngineeringChalmers University TechnologyGothenburgSweden

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