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https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1007/bfb005...
Part of book or chapter of book . 1998 . Peer-reviewed
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DBLP
Conference object . 2017
Data sources: DBLP
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A stabilizing repair timer

Authors: Ted Herman;

A stabilizing repair timer

Abstract

Certain types of system faults, notably data errors due to transient faults, can be repaired by software. The repair consists of identifying faulty variables and then rewriting data to correct the fault. If fault identification is imprecise, repair procedures can contaminate non faulty processes from data originating at faulty processes. This contamination danger is resolved by delaying data correction for a sufficiently long period. In order to delay correction, processes use a repair timer. This paper considers the problem of how asynchronous processes can implement a repair timer that is itself subject to faults. The main results are requirement specifications for a distributed repair timer and a repair timer algorithm. The algorithm self-stabilizes in O(D) rounds, where D is the diameter of the network, and provides reliable timing from k-faulty configurations within O(k) rounds.

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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!
2
Average
Average
Average
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