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ThinkMind // ICAS 2012, The Eighth International Conference on Autonomic and Autonomous Systems // View article icas_2012_3_20_20097


Online Spectrum-based Fault Localization for Health Monitoring and Fault Recovery of Self-Adaptive Systems

Authors:
Éric Piel
Alberto Gonzalez-Sanchez
Hans-Gerhard Gross
Arjan J.C. van Gemund
Rui Abreu

Keywords: Fault localization, diagnosis, self-awareness, autonomous system, monitoring, component-based system

Abstract:
Software systems used in the industry are often large and complex. Even with an extensive validation phase, it is impossible to ensure that a software system is fault-free and will remain so all along its evolution. When a failure happens in operation, the time to solve the fault should be minimized. The major challenge in this realm is the localization of a fault in one of the constituent components of the overall system. We strive at simplifying the localization of the fault that led to a failure by adapting existing techniques to the online context in such a way that allows the system to be aware of its own internal faults and react to it. This article first proposes to apply the Spectrum-based Fault Localization (SFL) method for online fault localization and health monitoring. Several implementation approaches are presented with a performance that depends on the architecture and the framework used. Evaluation is done through simulation of online failure scenarios, and through implementation in a demonstration surveillance system. The results of the studies performed confirm that applying SFL online, using monitoring, can successfully provide health information and locate problematic components, so that a software failure can be addressed adequately and timely.

Pages: 64 to 73

Copyright: Copyright (c) IARIA, 2012

Publication date: March 25, 2012

Published in: conference

ISSN: 2308-3913

ISBN: 978-1-61208-187-8

Location: St. Maarten, The Netherlands Antilles

Dates: from March 25, 2012 to March 30, 2012

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