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Fault identification in networks by passive testing

Authors: Raymond E. Miller; Khaled A. Arisha;

Fault identification in networks by passive testing

Abstract

We employ the finite state machine (FSM) model for networks to investigate fault identification using passive testing. First we introduce the concept of passive testing. Then, we introduce the FSM model with necessary assumptions and justification. We introduce the fault model and the fault detection algorithm using passive testing. Extending this result, we develop the theorems and algorithms for fault identification. An example is given illustrating our approach. Then, extensions to our approach are introduced to achieve better fault identification. We then illustrate our technique through a simulation of a practical X.25 example. Finally future extensions and potential trends are discussed.

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
Found an issue? Give us feedback
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!
17
Average
Top 10%
Top 10%
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