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Randomization and failure detection: A hybrid approach to solve Consensus

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Distributed Algorithms (WDAG 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1151))

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Abstract

We present a Consensus algorithm that combines randomization and unreliable failure detection, two well-known techniques for solving Consensus in asynchronous systems with crash failures. This hybrid algorithm combines advantages from both approaches: it guarantees deterministic termination if the failure detector is accurate, and probabilistic termination otherwise. In executions with no failures or failure detector mistakes, the most likely ones in practice, Consensus is reached in only two asynchronous rounds.

Research partially supported by NSF grant CCR-9402896, by DARPA/NASA Ames grant NAG-2-593, and by an Olin Fellowship.

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References

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Authors and Affiliations

  1. Computer Science Department, Cornell University, 14853-7501, Ithaca, NY, USA

    Marcos Kawazoe Aguilera & Sam Toueg

Authors
  1. Marcos Kawazoe Aguilera
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  2. Sam Toueg
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Editor information

Özalp Babaoğlu Keith Marzullo

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© 1996 Springer-Verlag Berlin Heidelberg

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Aguilera, M.K., Toueg, S. (1996). Randomization and failure detection: A hybrid approach to solve Consensus. In: Babaoğlu, Ö., Marzullo, K. (eds) Distributed Algorithms. WDAG 1996. Lecture Notes in Computer Science, vol 1151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61769-8_3

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  • DOI: https://doi.org/10.1007/3-540-61769-8_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61769-3

  • Online ISBN: 978-3-540-70679-3

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