What is recorded here?
Chandra and Toueg define unreliable failure detectors through completeness and accuracy, construct crash-tolerant consensus algorithms using them, and reduce consensus and atomic broadcast to one another under the stated asynchronous model. A timeout supplies a suspicion, not proof that another computer has stopped. The paper makes that distinction part of the system model: a failure detector may repeatedly accuse working processes yet still provide enough limited information for a carefully designed consensus algorithm. Its abstraction separates application reasoning from the detector’s physical implementation. Different accuracy assumptions tolerate different numbers of crashes, and an eventually accurate detector still needs a correct majority for the stated message-passing solution. The algorithms preserve agreement without forcing falsely suspected correct processes to crash.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
The main model has fixed known processes, reliable pairwise channels, fair eventual delivery/steps and crash-stop failures without recovery, not arbitrary Byzantine behavior or Sybil membership. Perpetual and eventual accuracy are distinct: the eventual class used for consensus needs a strict correct majority; stronger perpetual accuracy can tolerate n-1 crashes. These are quantified history properties, not a measured detection-success percentage. The detector is additional information, so this does not refute FLP. Growing timeouts implement the claimed class only under additional timing assumptions; pure asynchrony permits endlessly recurring false suspicions. Initial message loss invalidates the unmodified Figure 6 consensus algorithm, as the paper explicitly notes. Some classification and appendix proofs are omitted/sketched; repentance depends on algorithm/knowledge and extends the earlier failure-pattern-only formalism. The weakest-detector necessity result belongs to a separately credited three-author companion. The read 44-page author manuscript has pagination placeholders; equality to every final publisher-page detail is unverified. Full proof/model checking and claimed implementation efficiency were not independently replayed. Agreement is not scientific correctness.
Read the original work
- Chandra and Toueg, Unreliable Failure Detectors for Reliable Distributed Systems: public44-page author manuscript
- MIT Journal of the ACM Bibliography: Chandra and Toueg1996 publication and abstract
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People and systems
Tushar Deepak Chandra; Sam Toueg
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English catalogue narrative
Chandra and Toueg: unreliable failure detectors for reliable systems
Chandra and Toueg define unreliable failure detectors through completeness and accuracy, construct crash-tolerant consensus algorithms using them, and reduce consensus and atomic broadcast to one another under the stated asynchronous model.
A timeout supplies a suspicion, not proof that another computer has stopped. The paper makes that distinction part of the system model: a failure detector may repeatedly accuse working processes yet still provide enough limited information for a carefully designed consensus algorithm. Its abstraction separates application reasoning from the detector’s physical implementation. Different accuracy assumptions tolerate different numbers of crashes, and an eventually accurate detector still needs a correct majority for the stated message-passing solution. The algorithms preserve agreement without forcing falsely suspected correct processes to crash.
Scientific scope
The main model has fixed known processes, reliable pairwise channels, fair eventual delivery/steps and crash-stop failures without recovery, not arbitrary Byzantine behavior or Sybil membership. Perpetual and eventual accuracy are distinct: the eventual class used for consensus needs a strict correct majority; stronger perpetual accuracy can tolerate n-1 crashes. These are quantified history properties, not a measured detection-success percentage. The detector is additional information, so this does not refute FLP. Growing timeouts implement the claimed class only under additional timing assumptions; pure asynchrony permits endlessly recurring false suspicions. Initial message loss invalidates the unmodified Figure 6 consensus algorithm, as the paper explicitly notes. Some classification and appendix proofs are omitted/sketched; repentance depends on algorithm/knowledge and extends the earlier failure-pattern-only formalism. The weakest-detector necessity result belongs to a separately credited three-author companion. The read 44-page author manuscript has pagination placeholders; equality to every final publisher-page detail is unverified. Full proof/model checking and claimed implementation efficiency were not independently replayed. Agreement is not scientific correctness.
People and systems
Tushar Deepak Chandra; Sam Toueg