State-machine replication for planet-scale systems
Main Author: | |
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Publication Date: | 2020 |
Other Authors: | , , , , |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/1822/71106 |
Summary: | 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. |
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State-machine replication for planet-scale systemsconsensusfault tolerancegeo-replicationScience & TechnologyOnline 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.H2020 - Horizon 2020 Framework Programme(825184)Association for Computing MachineryUniversidade do MinhoEnes, VitorBaquero, CarlosRezende, Tuanir FrançaGotsman, AlexeyPerrin, MatthieuSutra, Pierre20202020-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/71106engVitor 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/10.1145/3342195.3387543978-1-4503-6882-710.1145/3342195.3387543https://dl.acm.org/doi/10.1145/3342195.3387543info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T07:01:19Zoai:repositorium.sdum.uminho.pt:1822/71106Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:12:35.144656Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
State-machine replication for planet-scale systems |
title |
State-machine replication for planet-scale systems |
spellingShingle |
State-machine replication for planet-scale systems Enes, Vitor consensus fault tolerance geo-replication Science & Technology |
title_short |
State-machine replication for planet-scale systems |
title_full |
State-machine replication for planet-scale systems |
title_fullStr |
State-machine replication for planet-scale systems |
title_full_unstemmed |
State-machine replication for planet-scale systems |
title_sort |
State-machine replication for planet-scale systems |
author |
Enes, Vitor |
author_facet |
Enes, Vitor Baquero, Carlos Rezende, Tuanir França Gotsman, Alexey Perrin, Matthieu Sutra, Pierre |
author_role |
author |
author2 |
Baquero, Carlos Rezende, Tuanir França Gotsman, Alexey Perrin, Matthieu Sutra, Pierre |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Enes, Vitor Baquero, Carlos Rezende, Tuanir França Gotsman, Alexey Perrin, Matthieu Sutra, Pierre |
dc.subject.por.fl_str_mv |
consensus fault tolerance geo-replication Science & Technology |
topic |
consensus fault tolerance geo-replication Science & Technology |
description |
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. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020 2020-01-01T00:00:00Z |
dc.type.driver.fl_str_mv |
conference paper |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/71106 |
url |
http://hdl.handle.net/1822/71106 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
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 978-1-4503-6882-7 10.1145/3342195.3387543 https://dl.acm.org/doi/10.1145/3342195.3387543 |
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info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Association for Computing Machinery |
publisher.none.fl_str_mv |
Association for Computing Machinery |
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