In Search of the Holy Grail: Looking for the Weakest Failure Detector for Wait-Free Set Agreement

Raynal, Michel; Travers, Corentin

doi:10.1007/11945529_2

Cited by 27 publications

(32 citation statements)

References 21 publications

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“…Several papers have been devoted to determine the weakest failure detector to solve the set-agreement problem in a distributed system where any number of processes can fail by crashing [7,8,9,10]. In particular, Zieliński proved recently that anti-Ω -a failure detector that outputs id's of processes such that the id of at least one correct process is output only finitely many times -is the weakest failure detector for set-agreement in a shared memory system [10].…”

Section: Introductionmentioning

confidence: 99%

The Weakest Failure Detector for Message Passing Set-Agreement

Delporte-Gallet

Fauconnier

Guerraoui

et al. 2008

Lecture Notes in Computer Science

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Abstract. In the set-agreement problem, n processes seek to agree on at most n−1 different values. This paper determines the weakest failure detector to solve this problem in a message-passing system where processes may fail by crashing. This failure detector, called the Loneliness detector and denoted L, outputs one of two values, "true" or "false" such that:(1) there is at least one process where L outputs always "false", and (2) if only one process is correct, L eventually outputs "true" at this process.

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Section: Introductionmentioning

confidence: 99%

The Weakest Failure Detector for Message Passing Set-Agreement

Delporte-Gallet

Fauconnier

Guerraoui

et al. 2008

Lecture Notes in Computer Science

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“…This failure detector has been proposed independently in [11] and [23]. It is used in [11] to boost an obstruction-free object implementation into a non-blocking implementation and it is also shown that this failure detector is the weakest that allows such a boosting.…”

Section: Lemma 4 No Two Processes Decide Different Valuesmentioning

confidence: 99%

“…It is used in [11] to boost an obstruction-free object implementation into a non-blocking implementation and it is also shown that this failure detector is the weakest that allows such a boosting. It is used in [23] to solve the k-set agreement problem when the participating processes can be any subset of processes.…”

Section: Lemma 4 No Two Processes Decide Different Valuesmentioning

confidence: 99%

From a Store-Collect Object and Ω to Efficient Asynchronous Consensus

Raynal

Stainer

2012

Euro-Par 2012 Parallel Processing

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This paper presents an efficient algorithm that builds a consensus object. This algorithm is based on an Ω failure detector (to obtain consensus liveness) and a store-collect object (to maintain its safety). A store-collect object provides the processes with two operations, a store operation which allows the invoking process to deposit a new value while discarding the previous value it has deposited and a collect operation that returns to the invoking process a set of pairs (i, val) where val is the last value deposited by the process p i . A store-collect object has no sequential specification.While store-collect objects have been used as base objects to design wait-free constructions of more sophisticated objects (such as snapshot or renaming objects), as far as we know, they have not been explicitly used to built consensus objects. The proposed storecollect-based algorithm, which is round-based, has several noteworthy features. First it uses a single store-collect object (and not an object per round). Second, during a round, a process invokes at most once the store operation and the value val it deposits is a simple pair r, v where r is a round number and v a proposed value. Third, a process is directed to skip rounds according to its view of the current global state (thereby saving useless computation rounds). Finally, the algorithm benefits from the adaptive wait-free implementations that have been proposed for store-collect objects, namely, the number of shared memory accesses involved in a collect operation is O(k) where k is the number of processes that have invoked the store operation. This makes the proposed algorithm particularly efficient and interesting for multiprocess programs made up of asynchronous crash-prone processes that run on top of multicore architectures. Key-words:asynchronous shared memory system, building block, concurrent object, consensus, distributed algorithm, eventual leader, failure detector, fault-tolerance, modularity, multicore system, process crash, store-collect object Consensus asynchrone efficace à partir des objets distribués Ω et Store-collect Résumé : Cet article présente un algorithme efficace qui implémente un objet consensus sans attente (wait-free). Cet algorithme s'appuie sur un détecteur de fautes Ω pour garantir la vivacité du consensus et sur un objet store-collect qui en assure la sûreté. Cette approche permet de bénéficier des implémentations adaptatives existantes de l'objet store-collect, ce qui fait de l'algorithme proposé une alternative intéressante pour résoudre le problème du consensus dans les systèmes asynchrones sujets aux défaillances construits sur des architectures multiprocesseur.

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“…We use the very existence of our algorithm to (a) disprove the conjecture of [14] about the weakest failure detector to implement n-resilient n-set agreement and (b) prove that implementing n-resilient n-set agreement with read/write objects is strictly weaker than solving n + 1-process consensus using n-process consensus.…”

Section: Introductionmentioning

confidence: 96%

“…Failure detector Ω n was shown to be sufficient to solve (1) n-resilient n-setagreement among n + 1 processes using registers [13], and (2) n + 1-process consensus using n-process consensus [16]. In fact, Ω n was also shown to be necessary to implement n + 1-process consensus using n-process consensus [9] and conjectured to be necessary to solve set-agreement [14]. It was our long quest to prove this conjecture that led us identify Υ and devise our set-agreement algorithm based on this oracle.…”

Section: Introductionmentioning

confidence: 99%

On the weakest failure detector ever

et al. 2009

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Many problems in distributed computing are impossible when no information about process failures is available. It is common to ask what information about failures is necessary and sufficient to circumvent some specific impossibility, e.g., consensus, atomic commit, mutual exclusion, etc. This paper asks what information about failures is needed to circumvent any impossibility and sufficient to circumvent some impossibility. In other words, what is the minimal yet non-trivial failure information.We present an abstraction, denoted Υ, that provides very little failure information. In every run of the distributed system, Υ eventually informs the processes that some set of processes in the system cannot be the set of correct processes in that run. Although seemingly weak, for it might provide random information for an arbitrarily long period of time, and it only excludes one possibility of correct set among many, Υ still captures non-trivial failure information. We show that Υ is sufficient to circumvent the fundamental wait-free set-agreement impossibility. While doing so, we (a) disprove previous conjectures about the weakest failure detector to solve set-agreement and we (b) prove that solving set-agreement with registers is strictly weaker than solving n + 1-process consensus using n-process consensus.We prove that Υ is, in a precise sense, minimal to circumvent any wait-free impossibility. Roughly, we show that Υ is the weakest eventually stable failure detector to circumvent

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In Search of the Holy Grail: Looking for the Weakest Failure Detector for Wait-Free Set Agreement

Cited by 27 publications

References 21 publications

The Weakest Failure Detector for Message Passing Set-Agreement

The Weakest Failure Detector for Message Passing Set-Agreement

From a Store-Collect Object and Ω to Efficient Asynchronous Consensus

On the weakest failure detector ever

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