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2017 | OriginalPaper | Buchkapitel

Agreement Functions for Distributed Computing Models

verfasst von : Petr Kuznetsov, Thibault Rieutord

Erschienen in: Networked Systems

Verlag: Springer International Publishing

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Abstract

The paper proposes a surprisingly simple characterization of a large class of models of distributed computing, via an agreement function: for each set of processes, the function determines the best level of set consensus these processes can reach. We show that the task computability of a large class of fair adversaries that includes, in particular superset-closed and symmetric one, is precisely captured by agreement functions.

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Fußnoten
1
In the “universal” task of consensus, every process has a private input value, and is expected to produce an output value, so that (validity) every output is an input of some process, (agreement) no two processes produce different output values, and (termination) every process taking sufficiently many steps returns.
 
2
Note that the extended BG-simulation provides a mechanism which ensures that a simulation step is not blocked forever by a no longer active BG simulator.
 
3
\(\mathcal {A}|_P\) is the adversary consisting of all live sets of \(\mathcal {A}\) that are subsets of P.
 
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Metadaten
Titel
Agreement Functions for Distributed Computing Models
verfasst von
Petr Kuznetsov
Thibault Rieutord
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-59647-1_14