A general framework to solve agreement problems

Hurfin, Michel; Macêdo, Raimundo José de Araújo; Raynal, Michel; Tronel, Frédéric

doi:10.1109/reldis.1999.805083

Cited by 48 publications

(32 citation statements)

References 10 publications

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“…The algorithm was adapted from the Chandra-Toueg Consensus algorithm using ♦S [8], and relies on the same assumptions. Even though we have not discussed this issue, other Consensus algorithms could also easily be adapted to solve Lazy Consensus (e.g., [22,30,35,36]). …”

Section: Resultsmentioning

confidence: 99%

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Semi-passive replication and Lazy Consensus

Défago¹,

Schiper²

2004

Journal of Parallel and Distributed Computing

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This paper presents two main contributions: semi-passive replication and Lazy Consensus. The former is a replication technique with parsimonious processing. It is based on the latter; a variant of Consensus allowing the lazy evaluation of proposed values.Semi-passive replication is a replication technique with parsimonious processing. This means that, in the normal case, each request is processed by only one single process. The most significant aspect of semi-passive replication is that it requires a weaker system model than existing techniques of the same family. For semi-passive replication, we give an algorithm based on the Lazy Consensus.Lazy Consensus is a variant of the Consensus problem that allows the lazy evaluation of proposed values, hence the name. The main difference with Consensus is the introduction of an additional property of laziness. This property requires that proposed values are computed only when they are actually needed. We present an algorithm based on Chandra and Toueg's Consensus algorithm for asynchronous distributed systems with a ♦S failure detector.

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Section: Resultsmentioning

confidence: 99%

“…The details of the proof are given in the appendix (pp. [22][23][24]. It is nevertheless important to note that Theorem 1.1 is proved independently of the laziness property of the Lazy Consensus.…”

Section: Parsimony Of the Semi-passive Replication Algorithmmentioning

confidence: 97%

Semi-passive replication and Lazy Consensus

Défago¹,

Schiper²

2004

Journal of Parallel and Distributed Computing

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“…While early implementations (Isis [5,6], Phoenix [17] and Totem [2], among others) were designed with a monolithic architecture, more recent systems (Horus [27], Ensemble [14], Transis [11], JavaGroups [3], Eden [15], and Fortika [18,19] 7 ) present a modular design. A comparison, from the architectural point of view, of most of these group communication toolkits can be found in [20].…”

Section: Related Workmentioning

confidence: 99%

“…However, this result is not comparable to current result due to significant differences in the system setup. Note that the Eden group communication toolkit [15] proposes a very similar technique.…”

Section: Related Workmentioning

confidence: 99%

On the Cost of Modularity in Atomic Broadcast

Rütti

Mena

Ekwall

et al. 2007

37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN'07)

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Modularity is a desirable property of complex software systems, since it simplifies code reuse, verification, maintenance, etc. However, the use of loosely coupled modules introduces a performance overhead. This overhead is often considered negligible, but this is not always the case. This paper aims at casting some light on the cost, in terms of performance, that is incurred when designing a relevant group communication protocol with modularity in mind: atomic broadcast.We conduct our experiments using two versions of atomic broadcast: a modular version and a monolithic one. We then measure the performance of both implementations under different system loads. Our results show that the overhead introduced by modularity is strongly related to the level of stress to which the system is subjected, and in the worst cases, reaches approximately 50%.

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“…Thus, over time, a sequence of consensus protocols is executed. It is possible to optimize the service by allowing a single execution of the consensus protocol to carry propositions from several distinct applications [9].…”

Section: Efficient and Robust Slowness Oraclementioning

confidence: 99%