Optimal discrimination between transient and permanent faults

Pizza, M.; Strigini, Lorenzo; Bondavalli, Andrea; Giandomenico, Felicita Di

doi:10.1109/hase.1998.731615

Cited by 17 publications

(11 citation statements)

References 15 publications

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“…The approach to diagnosis proposed in [9] tackles the problem in probabilistic terms and proposes an optimal discrimination (that is, having the highest possible accuracy) between transient and permanent faults by applying the Bayesian inference. Because of the similarities of the probabilistic view in approaching the diagnosis problem, we conduct here a comparison between our solution and the Bayesian one.…”

Section: Results On the Accuracy Of The Proposed Diagnosis Formalizationmentioning

confidence: 99%

“…The approach in [9] tackles optimal discrimination between transient and permanent faults based on applying Bayesian inference to the observed events (correct and erroneous results) and describing how the assessed probability that a component is permanently faulty varies with observed symptoms. We share the same probabilistic view and the construction of a formal framework based on well stated mathematical theories (Bayesian inference and hidden Markov models).…”

Section: Related Workmentioning

confidence: 99%

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Hidden Markov Models as a Support for Diagnosis: Formalization of the Problem and Synthesis of the Solution

Daidone

Giandomenico

Chiaradonna

et al. 2006

2006 25th IEEE Symposium on Reliable Distributed Systems (SRDS'06)

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In modern information infrastructures, diagnosis must be able to assess the status or the extent of the damage of individual components. Traditional one-shot diagnosis is not adequate, but streams of data on component behavior need to be collected and filtered over time as done by some existing heuristics. This paper proposes instead a general framework and a formalism to model such over-time diagnosis scenarios, and to find appropriate solutions. As such, it is very beneficial to system designers to support design choices. Taking advantage of the characteristics of the hidden Markov models formalism, widely used in pattern recognition, the paper proposes a formalization of the diagnosis process, addressing the complete chain constituted by monitored component, deviation detection and state diagnosis. Hidden Markov models are well suited to represent problems where the internal state of a certain entity is not known and can only be inferred from external observations of what this entity emits. Such over-time diagnosis is a first class representative of this category of problems. The accuracy of diagnosis carried out through the proposed formalization is then discussed, as well as how to concretely use it to perform state diagnosis and allow direct comparison of alternative solutions.

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Section: Results On the Accuracy Of The Proposed Diagnosis Formalizationmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Hidden Markov Models as a Support for Diagnosis: Formalization of the Problem and Synthesis of the Solution

Daidone

Giandomenico

Chiaradonna

et al. 2006

2006 25th IEEE Symposium on Reliable Distributed Systems (SRDS'06)

View full text Add to dashboard Cite

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“…As per the published statistics, the ratio between the frequencies of transient and permanent faults is found to vary from 4 to 1000 [16]. We follow Laprie's dependability concepts [17], [18] and assume that systems are exposed to these faults with probabilities depending on the characteristics of the systems and the environments that they are operating in.…”

Section: B Error Modelmentioning

confidence: 99%

Task-Level Probabilistic Scheduling Guarantees for Dependable Real-Time Systems - A Designer Centric Approach

Aysan

Dobrin

Punnekkat

2011

2011 14th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops

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Dependable real-time systems typically consist of tasks of mixed-criticality levels with associated fault tolerance (FT) requirements and scheduling them in a fault-tolerant manner to efficiently satisfy these requirements is a challenging problem. From the designers' perspective, the most natural way to specify the task criticalities is by expressing the reliability requirements at task level, without having to deal with low level decisions, such as deciding on which FT method to use, where in the system to implement the FT and the amount of resources to be dedicated to the FT mechanism. Hence, it is extremely important to devise methods for translating the highlevel requirement specifications for each task into the low-level scheduling decisions needed for the FT mechanism to function efficiently and correctly.In this paper, we focus achieving FT by redundancy in the temporal domain, as it is the commonly preferred method in embedded applications to recover from transient and intermittent errors, mainly due to its relatively low cost and ease of implementation. We propose a method which allows the system designer to specify task-level reliability requirements and provides a priori probabilistic scheduling guarantees for real-time tasks with mixed-criticality levels in the context of preemptive fixed-priority scheduling. We illustrate the method on a running example.

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“…We consider only transient bus faults. Transient faults, which persist for a short duration, are significantly more frequent than other faults in systems [15]. Permanent faults are a particular case of transient faults.…”

Section: Fault Modelmentioning

confidence: 99%

Reliable Fault-Tolerant Multi-bus Scheduling Algorithm

Arar¹,

Kalla²,

Kalla³

et al. 2013

IJCA

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In this paper, we propose a fault-tolerant scheduling real-time embedded system. This scheduling algorithm is dedicated to multi-bus heterogeneous architectures, which take as input a given system description and a given fault hypothesis. It is based on a data fragmentation and passive redundancy, which allow fast fault detection/retransmission and efficient use of buses. This scheduling approach consists of a list scheduling heuristic based on a Failure Rate Pressure. In order to maximize the reliability of the system, the scheduling of each fragmented data is depend on Failure Rate Pressure. Data fragmentation allows reliable communication and maximizes the reliability of the system. Finally, simulation results show the performance of our approach when using data fragmentation.

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Optimal discrimination between transient and permanent faults

Abstract: An important practical problem in fault diagnosis is dis-

Cited by 17 publications

References 15 publications

Hidden Markov Models as a Support for Diagnosis: Formalization of the Problem and Synthesis of the Solution

Hidden Markov Models as a Support for Diagnosis: Formalization of the Problem and Synthesis of the Solution

Task-Level Probabilistic Scheduling Guarantees for Dependable Real-Time Systems - A Designer Centric Approach

Reliable Fault-Tolerant Multi-bus Scheduling Algorithm

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