Enhanced fault-tolerance through Byzantine failure detection

Rida Bazzi, Maurice Herlihy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

We consider a variant of the Byzantine failure model in which Byzantine processes are eventually detected and silenced, and investigate the fault-tolerance of the classical broadcast and agreement problems. We show that if all Byzantine processes are eventually detected, then it is possible to solve the broadcast problem in the presence of any number of Byzantine processes. If only a fraction of the Byzantine processes can be detected, then we show that it is possible to solve consensus (and broadcast) if the total number of processes is N ≥ 2f + 3F + 1, where f is the number of Byzantine processes that are eventually detected and F is the number of those that are never detected. We show that 2f + 3F + 1 is a lower bound to solve the consensus and broadcast problems.

Original languageEnglish (US)
Title of host publicationPrinciples of Distributed Systems - 13th International Conference, OPODIS 2009, Proceedings
Pages129-143
Number of pages15
DOIs
StatePublished - Dec 31 2009
Event13th International Conference on Principles of Distributed Systems, OPODIS 2009 - Nimes, France
Duration: Dec 15 2009Dec 18 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5923 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th International Conference on Principles of Distributed Systems, OPODIS 2009
CountryFrance
CityNimes
Period12/15/0912/18/09

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Bazzi, R., & Herlihy, M. (2009). Enhanced fault-tolerance through Byzantine failure detection. In Principles of Distributed Systems - 13th International Conference, OPODIS 2009, Proceedings (pp. 129-143). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5923 LNCS). https://doi.org/10.1007/978-3-642-10877-8_12