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https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1007/bfb002...
Part of book or chapter of book . 2005 . Peer-reviewed
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DBLP
Conference object . 2017
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Replicated distributed processing

Authors: Santosh K. Shrivastava;

Replicated distributed processing

Abstract

Replicated processing with voting provides a powerful means of constructing highly reliable computing systems. We will consider a functionally distributed computing system intended for real-time applications, where each functional module — a node — has been configured in an NMR (N-modular redundant) fashion. Such a system receives processing requests from ‘actuators’ (the entities that demand services) that require distributed processing at various nodes. The paper will discuss various approaches to scheduling computations to ensure that each processor of an NMR node processes input messages in an identical order. The concept of exception handling for voters will be developed to detect failures in the system.

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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!
3
Average
Average
Average
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