Performance modelling of a fault-tolerant real-time multiprocessor using stochastic Petri nets

The fault-tolerant multiprocessor (ftmp) is a bus-based multiprocessor architecture with real-time and fault-tolerance features and is used in critical aerospace applications. A preliminary performance evaluation is of crucial importance in the design of such systems. In this paper, we review stochastic Petri nets (spn) and developspn-based performance models forftmp. These performance models enable efficient computation of important performance measures such as processing power, bus contention, bus utilization, and waiting times.     

Reliability and performance analysis of hardware–software systems with fault-tolerant software components

This paper presents an algorithm for evaluating reliability and expected execution time for systems consisting of fault-tolerant software components running on several hardware units. The components are built from functionally equivalent but independently developed versions characterized by different reliability and execution time. Different number of versions can be executed simultaneously depending on the number of available units. The system reliability is defined as the probability that the system produces a correct output in a specified time.     

Reliability and performance analysis for fault-tolerant programs consisting of versions with different characteristics

This paper presents a simple straightforward algorithm for evaluating reliability and expected execution time for software systems consisting of fault-tolerant components. The components are built from functionally equivalent but independently developed versions characterized by different reliability and performance. Both N-version programming (with parallel and sequential execution of the versions) and the recovery block scheme are considered within a universal model.     

Reliability estimation and prediction of multi-state components and coherent systems

This paper discusses the multi-state coherent system composed of multi-state components. First, using the min cut sets or min path sets, we present our simulation algorithm, instead of the general structure function, to calculate the probability that the system is in a specified state. Second, we check the components per period, e.g. one check per year, to obtain the state sequences of all components. When the state sequences are Markovian chains, we can predict the reliability of the components in several periods, such as the probability that the components are in specified states. Also, we give two methods to compute the system reliability in a number of periods: one employs the states of the components in these periods, which can be predicted by the state transition probability matrixes of the components; the other uses the state transition probability matrix of the system obtained by the simulated states of the components.     

An integrated methodology for the dynamic performance and reliability evaluation of fault-tolerant systems

We propose an integrated methodology for the reliability and dynamic performance analysis of fault-tolerant systems. This methodology uses a behavioral model of the system dynamics, similar to the ones used by control engineers to design the control system, but also incorporates artifacts to model the failure behavior of each component. These artifacts include component failure modes (and associated failure rates) and how those failure modes affect the dynamic behavior of the component. The methodology bases the system evaluation on the analysis of the dynamics of the different configurations the system can reach after component failures occur. For each of the possible system configurations, a performance evaluation of its dynamic behavior is carried out to check whether its properties, e.g., accuracy, overshoot, or settling time, which are called performance metrics, meet system requirements. Markov chains are used to model the stochastic process associated with the different configurations that a system can adopt when failures occur. This methodology not only enables an integrated framework for evaluating dynamic performance and reliability of fault-tolerant systems, but also enables a method for guiding the system design process, and further optimization. To illustrate the methodology, we present a case-study of a lateral-directional flight control system for a fighter aircraft.     

Reliability properties of systems with exchangeable components and exponential conditional distributions

We study basic properties for bivariate systems with exchangeable components and exponential conditional distributions which represent bi-component biological or engineering systems with structural dependency. This is equivalent to suppose that we have similar components with the bivariate exponential conditional joint distribution defined by Arnold and Strauss (1988). Specifically, we study the reliability functions, the moments, some aging measures, ordering and classification properties for series and parallel systems. Supported by Ministerio de Ciencia y Tecnología under grant BFM2003-02947     

Multi-scale reliability analysis and updating of complex systems by use of linear programming

Complex systems are characterized by large numbers of components, cut sets or link sets, or by statistical dependence between the component states. These measures of complexity render the computation of system reliability a challenging task. In this paper, a decomposition approach is described, which, together with a linear programming formulation, allows determination of bounds on the reliability of complex systems with manageable computational effort. The approach also facilitates multi-scale modeling and analysis of a system, whereby varying degrees of detail can be considered in the decomposed system. The paper also describes a method for computing bounds on conditional probabilities by use of linear programming, which can be used to update the system reliability for any given event. Applications to a power network demonstrate the methodology.     

Reliability and availability analysis of dependent-dynamic systems with DRBDs

Reliability/availability evaluation is an important, often indispensable, step in designing and analyzing (critical) systems, whose importance is constantly growing. When the complexity of a system is high, dynamic effects can arise or become significant. The system might be affected by dependent, cascade, on-demand and/or common cause failures, its units could interfere (load sharing, inter/sequence-dependency), and so on. It is also of great interest to evaluate redundancy and maintenance policies but, since dynamic behaviors usually do not satisfy the stochastic independence assumption, notations such as reliability block diagrams (RBDs), fault trees (FTs) or reliability graphs (RGs) become approximated/simplified techniques, unable to capture dynamic-dependent behaviors. To overcome such problem we developed a new formalism derived from RBDs: the dynamic RBDs (DRBDs). In this paper we explain how the DRBDs notation is able to adequately model and therefore analyze dynamic-dependent behaviors and complex systems. Particular emphasis is given to the modeling and the analysis phases, from both the theoretical and the practical point of views. Several case studies of dynamic-dependent systems, selected from literature and related to different application fields, are proposed. In this way we also compare the DRBDs approach with other methodologies, demonstrating its effectiveness.