EpTO: An Epidemic Total Order Algorithm for Large-Scale Distributed Systems
Miguel Matos, Hugues Mercier, Pascal Felber, Rui Oliveira & José Pereira
Résumé |
The ordering of events is a fundamental problem of distributed
computing and has been extensively studied over several decades.
From all the available orderings, total ordering is of particular
interest as it provides a powerful abstraction for building
reliable distributed applications. Unfortunately, deterministic
total order algorithms scale poorly and are therefore unfit for
modern large-scale applications. The main contribution of this
paper is EpTO, a total order algorithm with probabilistic agreement
that scales both in the number of processes and events. EpTO
provides deterministic safety and probabilistic liveness:
integrity, total order and validity are always preserved, while
agreement is achieved with arbitrarily high probability. We show
that EpTO is well-suited for large-scale dynamic distributed
systems: it does not require a global clock nor synchronized
processes, and it is highly robust even when the network suffers
from large delays and significant churn and message loss. |
Mots-clés |
large-scale distributed systems, data dissemination, total order, epidemic algorithm |
Citation | M. Matos, et al., "EpTO: An Epidemic Total Order Algorithm for Large-Scale Distributed Systems," in 2015 ACM/IFIP/USENIX Middleware conference, Vancouver, Canada, 2015. |
Type | Actes de congrès (Anglais) |
Nom de la conférence | 2015 ACM/IFIP/USENIX Middleware conference (Vancouver, Canada) |
Date de la conférence | 9-12-2015 |
URL | http://dx.doi.org/10.1145/2814576.2814804 |