Sciweavers

Share
INFOCOM
2002
IEEE

Increasing robustness of fault localization through analysis of lost, spurious, and positive symptoms

8 years 11 months ago
Increasing robustness of fault localization through analysis of lost, spurious, and positive symptoms
—This paper utilizes belief networks to implement fault localization in communication systems taking into account comprehensive information about the system behavior. Most previous work on this subject performs fault localization based solely on the information about malfunctioning system components (i.e., negative symptoms). In this paper, we show that positive information, i.e., the lack of any disorder in some system components, may be used to improve the accuracy of this process. The technique presented in this paper allows lost and spurious symptoms to be incorporated in the analysis. We show through simulation that in a noisy network environment the analysis of lost and spurious symptoms increases the robustness of fault localization with belief networks. We also demonstrate that belief networks yield high accuracy even for approximate probability input data and therefore are a promising model for non-deterministic fault localization.1
Malgorzata Steinder, Adarshpal S. Sethi
Added 15 Jul 2010
Updated 15 Jul 2010
Type Conference
Year 2002
Where INFOCOM
Authors Malgorzata Steinder, Adarshpal S. Sethi
Comments (0)
books