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Brief Announcement
Brief Announcement: Reaching Approximate Consensus When Everyone May Crash

Authors: Lewis Tseng, Qinzi Zhang, and Yifan Zhang

Published in: LIPIcs, Volume 179, 34th International Symposium on Distributed Computing (DISC 2020)


Abstract
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.

Cite as

Lewis Tseng, Qinzi Zhang, and Yifan Zhang. Brief Announcement: Reaching Approximate Consensus When Everyone May Crash. In 34th International Symposium on Distributed Computing (DISC 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 179, pp. 53:1-53:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@InProceedings{tseng_et_al:LIPIcs.DISC.2020.53,
  author =	{Tseng, Lewis and Zhang, Qinzi and Zhang, Yifan},
  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 =	{Attiya, Hagit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2020.53},
  URN =		{urn:nbn:de:0030-drops-131319},
  doi =		{10.4230/LIPIcs.DISC.2020.53},
  annote =	{Keywords: Approximate Consensus, Fair-loss Channel, Crash-recovery}
}
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