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https://hdl.handle.net/1822/71106
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Campo DC | Valor | Idioma |
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dc.contributor.author | Enes, Vitor | por |
dc.contributor.author | Baquero, Carlos | por |
dc.contributor.author | Rezende, Tuanir França | por |
dc.contributor.author | Gotsman, Alexey | por |
dc.contributor.author | Perrin, Matthieu | por |
dc.contributor.author | Sutra, Pierre | por |
dc.date.accessioned | 2021-03-30T22:46:28Z | - |
dc.date.available | 2021-03-30T22:46:28Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Vitor Enes, Carlos Baquero, Tuanir França Rezende, Alexey Gotsman, Matthieu Perrin, and Pierre Sutra. 2020. State-machine replication for planet-scale systems. In Proceedings of the Fifteenth European Conference on Computer Systems (EuroSys '20). Association for Computing Machinery, New York, NY, USA, Article 24, 1–15. DOI:https://doi.org/10.1145/3342195.3387543 | por |
dc.identifier.isbn | 978-1-4503-6882-7 | - |
dc.identifier.uri | https://hdl.handle.net/1822/71106 | - |
dc.description.abstract | Online applications now routinely replicate their data at multiple sites around the world. In this paper we present Atlas, the first state-machine replication protocol tailored for such planet-scale systems. Atlas does not rely on a distinguished leader, so clients enjoy the same quality of service independently of their geographical locations. Furthermore, client-perceived latency improves as we add sites closer to clients. To achieve this, Atlas minimizes the size of its quorums using an observation that concurrent data center failures are rare. It also processes a high percentage of accesses in a single round trip, even when these conflict. We experimentally demonstrate that Atlas consistently outperforms state-of-The-Art protocols in planet-scale scenarios. In particular, Atlas is up to two times faster than Flexible Paxos with identical failure assumptions, and more than doubles the performance of Egalitarian Paxos in the YCSB benchmark. | por |
dc.description.sponsorship | H2020 - Horizon 2020 Framework Programme(825184) | por |
dc.language.iso | eng | por |
dc.publisher | Association for Computing Machinery | por |
dc.rights | openAccess | por |
dc.subject | consensus | por |
dc.subject | fault tolerance | por |
dc.subject | geo-replication | por |
dc.title | State-machine replication for planet-scale systems | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://dl.acm.org/doi/10.1145/3342195.3387543 | por |
dc.date.updated | 2021-03-30T09:56:11Z | - |
dc.identifier.doi | 10.1145/3342195.3387543 | por |
dc.subject.wos | Science & Technology | por |
sdum.export.identifier | 10189 | - |
sdum.conferencePublication | Proceedings of the 15th European Conference on Computer Systems, EuroSys 2020 | por |
sdum.bookTitle | PROCEEDINGS OF THE FIFTEENTH EUROPEAN CONFERENCE ON COMPUTER SYSTEMS (EUROSYS'20) | por |
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Ficheiro | Descrição | Tamanho | Formato | |
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enes-atlas.pdf | 936,14 kB | Adobe PDF | Ver/Abrir |