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On the diagnosis of Byzantine faults

Authors: Joel C. Adams; K.V.S. Ramarao;

On the diagnosis of Byzantine faults

Abstract

The class of evidence-based diagnosis algorithms is developed to identify Byzantine (and any other faulty) processors. Such algorithms are said to be fair if they identify no failure-free processor as faulty. This paper makes two significant contributions: (i) it introduces a very general and simple formal model of the evidence-based diagnosis algorithms; and (ii) it derives a simple fair diagnosis algorithm, which is proved optimal for a large class of algorithms. It is further demonstrated that no fair evidence-based diagnosis algorithm can guarantee the identification of all faulty processors (completeness). Several insights into the behavior of the algorithm are presented. >

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    Average
    influence
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citations
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!
12
Average
Top 10%
Top 10%
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