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On-line failure prediction in safety-critical systems
- Publication Year :
- 2015
- Publisher :
- Elsevier, 2015.
-
Abstract
- In safety-critical systems such as Air Traffic Control system, SCADA systems, Railways Control Systems, there has been a rapid transition from monolithic systems to highly modular ones, using off-the-shelf hardware and software applications possibly developed by different manufactures. This shift increased the probability that a fault occurring in an application propagates to others with the risk of a failure of the entire safety-critical system. This calls for new tools for the on-line detection of anomalous behaviors of the system, predicting thus a system failure before it happens, allowing the deployment of appropriate mitigation policies.The paper proposes a novel architecture, namely CASPER, for online failure prediction that has the distinctive features to be (i) black-box: no knowledge of applications internals and logic of the system is required (ii) non-intrusive: no status information of the components is used such as CPU or memory usage; The architecture has been implemented to predict failures in a real Air Traffic Control System. CASPER exhibits high degree of accuracy in predicting failures with low false positive rate. The experimental validation shows how operators are provided with predictions issued a few hundred of seconds before the occurrence of the failure. Non-intrusive and black box effective online failure prediction.We monitor network traffic, only, to perform online failure prediction.Application agnostic: no knowledge of application logic is required.We use complex event processing to produce a representation of the system state.We use hidden Markov models in order to create a state recognizer.
- Subjects :
- Black box (phreaking)
Complex distributed systems
Computer science
business.industry
Computer Networks and Communications
Distributed computing
Complex event processing
Air traffic control
Modular design
Fault (power engineering)
Critical infrastructures
Life-critical system
SCADA
System failure
Software deployment
Failure prediction
Hardware and Architecture
Control system
Machine learning
Software
business
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....ff8f4437f3d9198dd2e55636e81191a5