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https://doi.org/10.1109/words....
Article . 2006 . Peer-reviewed
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https://dx.doi.org/10.1109/wor...
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Deterministic Scheduling for Multithreaded Replicas

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 11 Oct 2006Publisher:IEEEJournal:10th IEEE International Workshop on Object-Oriented Real-Time Dependable Systems
Authors: Wenbing Zhao 0001; Louise E. Moser; P. M. Melliar-Smith;

doi: 10.1109/words.2005.26

Deterministic Scheduling for Multithreaded Replicas

Abstract

Replication of objects, processes and components is essential for building reliable distributed systems. However, maintaining replica consistency in the presence of nondeterminism is a challenge. There are many sources of nondeterminism in the applications being replicated. In this paper, we focus on the nondeterminism resulting from multithreading in the applications, and present a deterministic scheduling algorithm for ensuring consistent execution of replicated multithreaded applications.

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    popularity
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    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
12
Average
Top 10%
Top 10%