The information structure of indulgent consensus

Guerraoui, Rachid; Raynal, Michel

doi:10.1109/tc.2004.1268403

Cited by 110 publications

(139 citation statements)

References 35 publications

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“…It follows that r, v is the only pair r, − stored in MEM at round r. Moreover, we have then r = rmax = r and, consequently, p i executes the lines [8][9][10][11][12]. If the predicate of line 9 is satisfied, p writes v into DEC which contradicts the fact that it executes an infinite number of rounds.…”

Section: Lemma 4 No Two Processes Decide Different Valuesmentioning

confidence: 96%

“…This means that the number of adopt-commit or weak set objects used in an execution cannot be bounded and, consequently, these objects have to be dynamically created 3 . Interestingly, alpha-based consensus algorithms (e.g., [10,12,17]) needs a single alpha object.…”

Section: Content Of the Papermentioning

confidence: 99%

“…if (r i = rmax i ) (8) then set i ← {v | r, v ∈ mem i where r ∈ {rmax i , rmax i − 1}}; (9) if (r i > 1) ∧ (set i = {est i }) (10) then DEC ← est i (11) else r i ← r i + 1 (12) end if (13) else est i ← v such that rmax i , v ∈ mem i ; r i ← rmax i (14) end if (15) end if (16) end while; (17) return(DEC ) end operation.…”

Section: Description Of the Algorithmmentioning

confidence: 99%

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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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Section: Lemma 4 No Two Processes Decide Different Valuesmentioning

confidence: 96%

Section: Content Of the Papermentioning

confidence: 99%

Section: Description Of the Algorithmmentioning

confidence: 99%

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

Raynal

Stainer

2012

Euro-Par 2012 Parallel Processing

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“…Omega was shown to be the weakest, in terms of information about failures, to solve consensus in a distributed system prone to process crashes but where a majority of processes are correct (which is the best, lower bound, that can be attained with Omega [5]). Several Omega-based consensus protocols have been proposed, e.g., [22,14,12,23] for message-passing systems, and [24] for shared memory systems. All these protocols are indulgent [2].…”

Section: The Omega Abstractionmentioning

confidence: 99%

“…Related work The spirit of our Alpha abstraction (implicitly hidden in [12] and inspired from the notion of 'eventual register' introduced in [13]) is close to the one of the Lambda abstraction we have investigated in [14]. Both are designed for round-based algorithms, and defined in an abstract way by a set of axiomatic properties.…”

Section: Introductionmentioning

confidence: 99%

The Alpha of Indulgent Consensus

Guerraoui¹,

Raynal²

2006

The Computer Journal

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This paper presents a simple framework unifying a family of consensus algorithms that can tolerate process crash failures and asynchronous periods of the network, also called indulgent consensus algorithms. Key to the framework is a new abstraction we introduce here, called Alpha, and which precisely captures consensus safety. Implementations of Alpha in shared memory, storage area network, message passing and active disk systems are presented, leading to directly derived consensus algorithms suited to these communication media. The paper also considers the case where the number of processes is unknown and can be arbitrarily large.

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Failure Detectors for Asynchronous Distributed Systems: An Introduction

Rennes

2008

Wiley Encyclopedia of Computer Science and Engineering

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Since the first version of Chandra and Toueg's seminal paper titled “ Unreliable failure detectors for reliable distributed systems ” in 1991, the failure detector concept has been extensively studied and investigated. This is not at all surprising as failure detection is pervasive in the design, the analysis, and the implementation of a lot of fault‐tolerant distributed algorithms that constitute the core of distributed system middleware. The literature on this topic is mostly technical and appears mainly in theoretically inclined journals and conferences. The aim of this article is to offer an introductory survey to the failure detector concept for readers who are not familiar with it and want to quickly understand its aim, its basic principles, its power, and is limitations. To attain this goal, the article first describes the motivations that underlie the concept, and then it surveys several distributed computing problems showing how they can be solved with the help of an appropriate failure detector. So, this short article presents motivations, concepts, problems, definitions, and algorithms (it does not contain proofs). It is aimed at people who want to understand the basics of failure detectors.

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The information structure of indulgent consensus

Cited by 110 publications

References 35 publications

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

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

The Alpha of Indulgent Consensus

Failure Detectors for Asynchronous Distributed Systems: An Introduction

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