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https://dx.doi.org/10.5075/epf...
Doctoral thesis . 2011
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Doctoral thesis
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Round-Based Consensus Algorithms, Predicate Implementations and Quantitative Analysis

Authors: Fatemeh Borran;

Round-Based Consensus Algorithms, Predicate Implementations and Quantitative Analysis

Abstract

Fault-tolerant computing is the art and science of building computer systems that continue to operate normally in the presence of faults. The fault tolerance field covers a wide spectrum of research area ranging from computer hardware to computer software. A common approach to obtain a fault-tolerant system is using software replication. However, maintaining the state of the replicas consistent is not an easy task, even though the understanding of the problems related to replication has significantly evolved over the past thirty years. Consensus is a fundamental building block to provide consistency in any fault-tolerant distributed system. A large number of algorithms have been proposed to solve the consensus problem in different systems. The efficiency of several consensus algorithms has been studied theoretically and practically. A common metric to evaluate the performance of consensus algorithms is the number of communication steps or the number of rounds (in round-based algorithms) for deciding. A large amount of improvements to consensus algorithms have been proposed to reduce this number under different assumptions, e.g., nice runs. However, the efficiency expressed in terms of number of rounds does not predict the time it takes to decide (including the time needed by the system to stabilize or not). Following this idea, the thesis investigates the round model abstraction to represent consensus algorithms, with benign and Byzantine faults, in a concise and modular way. The goal of the thesis is first to decouple the consensus algorithm from irrelevant details of implementations, such as synchronization, then study different possible implementations for a given consensus algorithm, and finally propose a more general analytical analysis for different consensus algorithms. The first part of the thesis considers the round-based consensus algorithms with benign faults. In this context, the round model allowed us to separate the consensus algorithms from the round implementation, to propose different round implementations, to improve existing round implementations by making them swift, and to provide quantitative analysis of different algorithms. The second part of the thesis considers the round-based consensus algorithms with Byzantine faults. In this context, there is a gap between theoretical consensus algorithms and practical Byzantine fault-tolerant protocols. The round model allowed us to fill the gap by better understanding existing protocols, and enabled us to express existing protocols in a simple and modular way, to obtain simplified proofs, to discover new protocols such as decentralized (non leader-based) algorithms, and finally to perform precise timing analysis to compare different algorithms. The last part of the thesis shows, as an example, how a round-based consensus algorithm that tolerates benign faults can be extended to wireless mobile ad hoc networks using an adequate communication layer. We have validated our implementation by running simulations in single hop and multi-hop wireless networks.

Keywords

distributed algorithms, modèle "heard-of", consensus problem, round model, partial synchrony, heard-of model, decentralized algorithms, algorithmes décentralisés, wireless ad hoc networks, consensus Byzantin, algorithmes en rondes, swift algorithms, système partiellement synchrone, problème de consensus, quantitative analysis, tolérance aux fautes, algorithmes distribués, Byzantine consensus, algorithmes avec leader, modèle en rondes, algorithmes "swift", round-based algorithms, analyse quantitative, leader-based algorithms, fault tolerance, réseau ad hoc sans fil

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average