Failure detectors in omission failure environments

Dolev, Danny; Friedman, Roy; Keidar, Idit; Malkhi, Dahlia

doi:10.1145/259380.259501

Cited by 66 publications

(63 citation statements)

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“…5 This is problematic because, in contrast to processes that permanently crash, unstable processes may continue to take steps, and so their incorrect suspicions may prevent the progress of some algorithms. For example, in the rotating coordinator consensus algorithms of [CT96,DFKM96,HMR97] if a process kept suspecting all processes then consensus would never be reached.…”

Section: Failure Detectors For the Crash-recovery Modelmentioning

confidence: 99%

“…The problem of solving consensus with failure detectors in systems where processes may recover from crashes was first addressed in [DFKM96] (with crash-recovery as a form of omission failures) and more recently studied in [OGS97,HMR97].…”

Section: Related Workmentioning

confidence: 99%

“…In [DFKM96,HMR97,OGS97], the question of whether stable storage is always necessary is not addressed, and all the algorithms use stable storage: in [DFKM96,OGS97], the entire state of the algorithm is recorded into stable storage at every state transition; in [HMR97], only a small part of the state is recorded, and writing to stable storage is done at most once per round. In this paper, we determine when stable storage is necessary, and give two matching consensus algorithms -with and without stable storage.…”

Section: Related Workmentioning

confidence: 99%

“…The algorithm in [DFKM96] is not designed to deal with unstable processes which may intermittently communicate with good ones.…”

Section: Related Workmentioning

confidence: 99%

“…In real systems, however, processes may recover after crashing and links may lose messages. In this paper, we focus on solving consensus with failure detectors in such systems, a problem that was first considered in [DFKM96,OGS97,HMR97] (a brief comparison with these works is in Section 1.3).…”

Section: Introductionmentioning

confidence: 99%

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Failure detection and consensus in the crash-recovery model

Aguilera

Chen²,

Toueg

2000

Distributed Computing

141

143

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We study the problems of failure detection and consensus in asynchronous systems in which processes may crash and recover, and links may lose messages. We first propose new failure detectors that are particularly suitable to the crash-recovery model. We next determine under what conditions stable storage is necessary to solve consensus in this model. Using the new failure detectors, we give two consensus algorithms that match these conditions: one requires stable storage and the other does not. Both algorithms tolerate link failures and are particularly efficient in the runs that are most likely in practice -those with no failures or failure detector mistakes. In such runs, consensus is achieved within 3δ time and with 4n messages, where δ is the maximum message delay and n is the number of processes in the system.

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Section: Failure Detectors For the Crash-recovery Modelmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

“…The algorithm in [DFKM96] is not designed to deal with unstable processes which may intermittently communicate with good ones.…”

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Failure detection and consensus in the crash-recovery model

Aguilera

Chen²,

Toueg

2000

Distributed Computing

141

143

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Increasing the Resilience of Distributed and Replicated Database Systems

Keidar

Dolev

1998

Journal of Computer and System Sciences

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This paper presents a new atomic commitment protocol, enhanced three phase commit (E3PC), that always allows a quorum in the system to make progress. Previously suggested quorum-based protocols (e.g., the quorum-based three phase commit (3PC) (Skeen, 1982)), allow a quorum to make progress in case of one failure. If failures cascade, however, and the quorum in the system is``lost'' (i.e., at a given time no quorum component exists), a quorum can later become connected and still remain blocked. With our protocol, a connected quorum never blocks. E3PC is based on the quorum-based 3PC (Skeen, 1982), and it does not require more time or communication than 3PC. We describe how this protocol can be exploited in a replicated database setting, making the database always available to a majority of the sites. ] 1998 Academic Press

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Failure Detection with Booting in Partially Synchronous Systems

Widder

Lann

Schmid

2005

Dependable Computing - EDCC 5

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Abstract. Unreliable failure detectors are a well known means to enrich asynchronous distributed systems with time-free semantics that allow to solve consensus in the presence of crash failures. Implementing unreliable failure detectors requires a system that provides some synchrony, typically an upper bound on end-to-end message delays. Recently, we introduced an implementation of the perfect failure detector in a novel partially synchronous model, referred to as the Θ-Model, where only the ratio Θ of maximum vs. minimum end-to-end delay of messages that are simultaneously in transit must be known a priori (while the actual delays need not be known and not even be bounded). In this paper, we present an alternative failure detector algorithm, which is based on a clock synchronization algorithm for the Θ-Model. It not only surpasses our first implementation with respect to failure detection time, but also works during the system booting phase.

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Failure detectors in omission failure environments

Cited by 66 publications

References 0 publications

Failure detection and consensus in the crash-recovery model

Failure detection and consensus in the crash-recovery model

Increasing the Resilience of Distributed and Replicated Database Systems

Failure Detection with Booting in Partially Synchronous Systems

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