State-Machine Replication for Planet-Scale Systems

Vitor Enes , Carlos Baquero , Tuanir França Rezende , Alexey Gotsman , Matthieu Perrin (1, 2) , Pierre Sutra

1 LS2N - équipe GDD - Gestion de Données Distribuées
2 LS2N - Laboratoire des Sciences du Numérique de Nantes

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.

Mots clés: Fault tolerance; Consensus; Geo-replication

Domaines: Calcul parallèle, distribué et partagé [cs.DC]

Vitor Enes, Carlos Baquero, Tuanir França Rezende, Alexey Gotsman, Matthieu Perrin, et al.. State-Machine Replication for Planet-Scale Systems. EuroSys 2020, Apr 2020, Heraklion, Greece. ⟨10.1145/3342195.3387543⟩. ⟨hal-02941693⟩