License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.DISC.2020.53
URN: urn:nbn:de:0030-drops-131319
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Tseng, Lewis ; Zhang, Qinzi ; Zhang, Yifan

Brief Announcement: Reaching Approximate Consensus When Everyone May Crash

LIPIcs-DISC-2020-53.pdf (0.4 MB)


Fault-tolerant consensus is of great importance in distributed systems. This paper studies the asynchronous approximate consensus problem in the crash-recovery model with fair-loss links. In our model, up to f nodes may crash forever, while the rest may crash intermittently. Each node is equipped with a limited-size persistent storage that does not lose data when crashed. We present an algorithm that only stores three values in persistent storage - state, phase index, and a counter.

BibTeX - Entry

  author =	{Lewis Tseng and Qinzi Zhang and Yifan Zhang},
  title =	{{Brief Announcement: Reaching Approximate Consensus When Everyone May Crash}},
  booktitle =	{34th International Symposium on Distributed Computing (DISC 2020)},
  pages =	{53:1--53:3},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-168-9},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{179},
  editor =	{Hagit Attiya},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-131319},
  doi =		{10.4230/LIPIcs.DISC.2020.53},
  annote =	{Keywords: Approximate Consensus, Fair-loss Channel, Crash-recovery}

Keywords: Approximate Consensus, Fair-loss Channel, Crash-recovery
Collection: 34th International Symposium on Distributed Computing (DISC 2020)
Issue Date: 2020
Date of publication: 07.10.2020

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