2026-08-05T06:50:18Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:13131 2024-03-06T10:51:38Z ddc:004 open_access

Brief Announcement: Reaching Approximate Consensus When Everyone May Crash Tseng, Lewis Zhang, Qinzi Zhang, Yifan Approximate Consensus Fair-loss Channel Crash-recovery 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Lewis Tseng and Qinzi Zhang and Yifan Zhang 2020 Is Part Of LIPIcs, Volume 179, 34th International Symposium on Distributed Computing (DISC 2020) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.DISC.2020.53 urn:nbn:de:0030-drops-131319 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2020.53 eng https://creativecommons.org/licenses/by/3.0/legalcode