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IEEE Transactions on Dependable and Secure Computing
Article . 2012 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
DBLP
Article . 2012
Data sources: DBLP
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Quantitative Analysis of Consensus Algorithms

Authors: Fatemeh Borran; Martin Hutle; Nuno Santos; André Schiper;

Quantitative Analysis of Consensus Algorithms

Abstract

Consensus is one of the key problems in fault-tolerant distributed computing. Although the solvability of consensus is now a well-understood problem, comparing different algorithms in terms of efficiency is still an open problem. In this paper, we address this question for round-based consensus algorithms using communication predicates, on top of a partial synchronous system that alternates between good and bad periods (synchronous and nonsynchronous periods). Communication predicates together with the detailed timing information of the underlying partially synchronous system provide a convenient and powerful framework for comparing different consensus algorithms and their implementations. This approach allows us to quantify the required length of a good period to solve a given number of consensus instances. With our results, we can observe several interesting issues, such as the number of rounds of an algorithm is not necessarily a good metric for its performance.

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    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.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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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!
7
Average
Top 10%
Top 10%
bronze