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Batista_2022_Else_jpdc
Journal article

Early scheduling on steroids : boosting parallel state machine replication

  • Batista, Eliã ORCID Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera - Escola Politécnica, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil
  • Alchieri, Eduardo ORCID Departamento de Ciência da Computacão, Universidade de Brasília, Campus Darcy Ribeiro, Asa Norte, Brasília, Brazil
  • Dotti, Fernando Escola Politécnica, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil
  • Pedone, Fernando ORCID Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
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  • 2022
Published in:
  • Journal of Parallel and Distributed Computing. - 2022, vol. 163, p. 269–282
State machine replication
Synchronization
Work-stealing
Scheduling
English State machine replication (SMR) is a standard approach to fault tolerance in which replicas execute requests deterministically and often serially. For performance, some techniques allow concurrent execution of requests in SMR while keeping determinism. Such techniques exploit the fact that independent requests can execute concurrently. A promising category of early scheduling solutions trades scheduling freedom for simplicity, allowing to expedite decisions during scheduling. This paper generalizes early scheduling and proposes a general method to schedule requests to threads, restricting scheduling overhead. Moreover, it explores improvements to the original early scheduling mechanism, namely the use of busy-wait synchronization and work-stealing techniques. We integrate early scheduling and its proposed improvements to a popular SMR framework. Performance results of the basic mechanism and its improvements are presented and compared to more classic approaches, where it is shown that early scheduling with our proposed enhancements can outperform the original early scheduling and other systems by a large margin in many scenarios.
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Language
  • English
Classification
Computer science and technology
License
CC BY-NC-ND
Open access status
hybrid
Identifiers
Persistent URL
https://n2t.net/ark:/12658/srd1322466
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