PSYNC: A Partially Synchronous Language for Fault-Tolerant Distributed Algorithms

Abstract : Fault-tolerant distributed algorithms play an important role in many critical/high-availability applications. These algorithms are notoriously difficult to implement correctly, due to asynchronous communication and the occurrence of faults, such as the network dropping messages or computers crashing. We introduce PSYNC, a domain specific language based on the Heard-Of model, which views asynchronous faulty systems as synchronous ones with an adversarial environment that simulates asyn-chrony and faults by dropping messages. We define a runtime system for PSYNC that efficiently executes on asynchronous networks. We formalize the relation between the runtime system and PSYNC in terms of observational refinement. The high-level lockstep abstraction introduced by PSYNC simplifies the design and implementation of fault-tolerant distributed algorithms and enables automated formal verification. We have implemented an embedding of PSYNC in the SCALA programming language with a runtime system for asynchronous networks. We show the applicability of PSYNC by implementing several important fault-tolerant distributed algorithms and we compare the implementation of consensus algorithms in PSYNC against implementations in other languages in terms of code size, runtime efficiency, and verification.
Type de document :
Communication dans un congrès
POPL, Jan 2017, Saint Petersburg United States. 2016, 〈10.1145/nnnnnnn.nnnnnnn〉
Liste complète des métadonnées

Littérature citée [69 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01434325
Contributeur : Cezara Dragoi <>
Soumis le : vendredi 13 janvier 2017 - 11:43:57
Dernière modification le : jeudi 26 avril 2018 - 10:29:01
Document(s) archivé(s) le : vendredi 14 avril 2017 - 19:44:53

Fichier

head.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Cezara Drăgoi, Thomas Henzinger, Damien Zufferey. PSYNC: A Partially Synchronous Language for Fault-Tolerant Distributed Algorithms. POPL, Jan 2017, Saint Petersburg United States. 2016, 〈10.1145/nnnnnnn.nnnnnnn〉. 〈hal-01434325〉

Partager

Métriques

Consultations de la notice

225

Téléchargements de fichiers

55