Fault Injection for Embedded Microprocessor-based Systems

Microprocessor-based embedded systems are increasingly used to control safety-critical systems (e.g., air and railway traffic control, nuclear plant control, aircraft and car control). In this case, fault tolerance mechanisms are introduced at the hardware and software level. Debugging and verifying the correct design and implementation of these mechanisms ask for effective environments, and Fault Injection represents a viable solution for their implementation. In this paper we present a Fault Injection environment, named FlexFI, suitable to assess the correctness of the design and implementation of the hardware and software mechanisms existing in embedded microprocessor-based systems, and to compute the fault coverage they provide. The paper describes and analyzes different solutions for implementing the most critical modules, which differ in terms of cost, speed, and intrusiveness in the original system behavio

Experimental analysis of computer system dependability

This paper reviews an area which has evolved over the past 15 years: experimental analysis of computer system dependability. Methodologies and advances are discussed for three basic approaches used in the area: simulated fault injection, physical fault injection, and measurement-based analysis. The three approaches are suited, respectively, to dependability evaluation in the three phases of a system's life: design phase, prototype phase, and operational phase. Before the discussion of these phases, several statistical techniques used in the area are introduced. For each phase, a classification of research methods or study topics is outlined, followed by discussion of these methods or topics as well as representative studies. The statistical techniques introduced include the estimation of parameters and confidence intervals, probability distribution characterization, and several multivariate analysis methods. Importance sampling, a statistical technique used to accelerate Monte Carlo simulation, is also introduced. The discussion of simulated fault injection covers electrical-level, logic-level, and function-level fault injection methods as well as representative simulation environments such as FOCUS and DEPEND. The discussion of physical fault injection covers hardware, software, and radiation fault injection methods as well as several software and hybrid tools including FIAT, FERARI, HYBRID, and FINE. The discussion of measurement-based analysis covers measurement and data processing techniques, basic error characterization, dependency analysis, Markov reward modeling, software-dependability, and fault diagnosis. The discussion involves several important issues studies in the area, including fault models, fast simulation techniques, workload/failure dependency, correlated failures, and software fault tolerance

Dependability analysis of web services

Web Services form the basis of the web based eCommerce eScience applications so it is vital that robust services are developed. Traditional validation and verification techniques are centred around the concept of removing all faults to guarantee correct operation whereas Dependability gives an assessment of how dependably a system can deliver the required functionality by assessing attributes, and by eliminating threats via means attempts to improve dependability. Fault injection is a well-proven dependability assessment method. Although much work has been done in the area of fault injection and distributed systems in general, there appears to have been little research carried out on applying this to middleware systems and Web Services in particular. There are additional problems associated with applying existing fault injection technologies to Web Services running in a virtual machine environment since most are either invasive or work at a machine level. The Fault Injection Technology (FIT) method has been devised to address these problems for middleware systems. The Web Service-Fault Injection Technology (WS-FIT) implementation applies the FIT method, based on network level fault injection, to Web Services to create a non-invasive dependability assessment method. It allows targeted perturbation of Web Service RFC parameters as well as more traditional network level fault injection operations. The WS-FIT tool includes taxonomies that define a system under test, fault models to apply and failure modes to be detected, and uses these taxonomies to generate fault injection campaigns. WS-FIT has been applied to a number of case studies and has successfully demonstrated its effectiveness. It has also been successfully applied to a third-party system to evaluate dependability means. It performed this dependability assessment as well as allowing debugging of the means to be undertaken uncovering unknown faults

Fault diagnosis by multisensor data: A data-driven approach based on spectral clustering and pairwise constraints

This paper deals with clustering based on feature selection of multisensor data in high-dimensional space. Spectral clustering algorithms are efficient tools in signal processing for grouping datasets sampled by multisensor systems for fault diagnosis. The effectiveness of spectral clustering stems from constructing an embedding space based on an affinity matrix. This matrix shows the pairwise similarity of the data points. Clustering is then obtained by determining the spectral decomposition of the Laplacian graph. In the manufacturing field, clustering is an essential strategy for fault diagnosis. In this study, an enhanced spectral clustering approach is presented, which is augmented with pairwise constraints, and that results in efficient identification of fault scenarios. The effectiveness of the proposed approach is described using a real case study about a diesel injection control system for fault detection