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Brief Annoucement: On Extending Brandt’s Speedup Theorem from LOCAL to Round-Based Full-Information Models

Authors Paul Bastide, Pierre Fraigniaud

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ACM Subject Classification
  • Theory of computation → Distributed algorithms
Keywords
  • Local Checkability
  • Distributed Complexity and Computability

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Abstract

Given any task Π, Brandt’s speedup theorem (PODC 2019) provides a mechanical way to design another task Π' on the same input-set as Π such that, for any t ≥ 1, Π is solvable in t rounds in the LOCAL model if and only if Π' is solvable in t-1 rounds in the LOCAL model. We dissect the construction in Brandt’s speedup theorem for expressing it in the broader framework of all round-based models supporting full information protocols, which includes models as different as asynchronous wait-free shared-memory computing with iterated immediate snapshots, and synchronous failure-free network computing.

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Paul Bastide and Pierre Fraigniaud. Brief Annoucement: On Extending Brandt’s Speedup Theorem from LOCAL to Round-Based Full-Information Models. In 35th International Symposium on Distributed Computing (DISC 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 209, pp. 47:1-47:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021) https://doi.org/10.4230/LIPIcs.DISC.2021.47

Author Details

Paul Bastide
  • Ecole Normale Supérieure de Rennes, France
Pierre Fraigniaud
  • Université de Paris and CNRS, France

Acknowledgements

Additional supports from ANR Project DUCAT.

References

  1. Hagit Attiya and Jennifer Welch. Distributed Computing: Fundamentals, Simulations, and Advanced Topics. Series on Parallel and Distributed Computing. Wiley, 2004. Google Scholar
  2. Paul Bastide and Pierre Fraigniaud. On extending Brandt’s speedup theorem from LOCAL to round-based full-information models, 2021. URL: http://arxiv.org/abs/2108.01989.
  3. Sebastian Brandt. An automatic speedup theorem for distributed problems. In 38th ACM Symposium on Principles of Distributed Computing (PODC), pages 379-388, 2019. URL: https://doi.org/10.1145/3293611.3331611.
  4. Nathan Linial. Locality in distributed graph algorithms. SIAM J. Comput., 21(1):193-201, 1992. URL: https://doi.org/10.1137/0221015.
  5. David Peleg. Distributed Computing: A Locality-Sensitive Approach. Discrete Mathematics and Applications. SIAM, 2000. Google Scholar
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