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
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/13131/
Tseng, Lewis ;
Zhang, Qinzi ;
Zhang, Yifan
Brief Announcement: Reaching Approximate Consensus When Everyone May Crash
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.
BibTeX - Entry
@InProceedings{tseng_et_al:LIPIcs:2020:13131,
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 = {https://drops.dagstuhl.de/opus/volltexte/2020/13131},
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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Keywords: |
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Approximate Consensus, Fair-loss Channel, Crash-recovery |
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Collection: |
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34th International Symposium on Distributed Computing (DISC 2020) |
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Issue Date: |
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2020 |
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Date of publication: |
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07.10.2020 |
