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Cutoffs for Symmetric Point-to-Point Distributed Algorithms

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Book cover Networked Systems (NETYS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 12129))

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Abstract

Distributed algorithms are typically parameterized in the number of participants. While in general, parameterized verification is undecidable, many distributed algorithms such as mutual exclusion, cache coherence, and distributed consensus enjoy the cutoff property, which reduces the parameterized verification problem to verification of a finite number of instances. Failure detection algorithms do not fall into one of the known classes. While consensus algorithms, for instance, are quorum-based, failure detectors typically rely on point-to-point communication and timeouts. In this paper, we formalize this communication structure and introduce the class of symmetric point-to-point algorithms. We show that the symmetric point-to-point algorithms have a cutoff. As a result, one can verify them by model checking small instances. We demonstrate the feasibility of our approach by specifying the failure detector by Chandra and Toueg in \(\textsc {TLA}^+\), and by model checking them with the TLC and the APALACHE model checkers.

Supported by Interchain Foundation (Switzerland) and the Austrian Science Fund (FWF) via the Doctoral College LogiCS W1255.

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Notes

  1. 1.

    Our specification is available at https://github.com/banhday/netys20.git.

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Authors and Affiliations

  1. TU Wien, Vienna, Austria

    Thanh-Hai Tran

  2. Informal Systems, Vienna, Austria

    Igor Konnov & Josef Widder

Authors
  1. Thanh-Hai Tran
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  2. Igor Konnov
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  3. Josef Widder
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Correspondence to Igor Konnov .

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Editors and Affiliations

  1. University of Cyprus, Nicosia, Cyprus

    Chryssis Georgiou

  2. Max Planck Institute for Software Systems, Kaiserslautern, Germany

    Rupak Majumdar

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Tran, TH., Konnov, I., Widder, J. (2021). Cutoffs for Symmetric Point-to-Point Distributed Algorithms. In: Georgiou, C., Majumdar, R. (eds) Networked Systems. NETYS 2020. Lecture Notes in Computer Science(), vol 12129. Springer, Cham. https://doi.org/10.1007/978-3-030-67087-0_21

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  • DOI: https://doi.org/10.1007/978-3-030-67087-0_21

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