The hybrid automated reliability predictor
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Dugan, J. B.↗
Engineering topics
Geist, R. M.
Publications and source records attributed to Geist, R. M..
Provably conservative approximations to complex reliability models
Complex models can be the bases for derivation of provably conservative and optimistic reliability models that incorporate a reduced state space and fewer transitions; they accordingly possess solutions that are more cost-effective than those of the original complex models. Design space can thereby be extensively explored without incurring the expense of multiple complex model solutions. A conservative-optimistic pair of derived models produces a band that includes the solution to the complex model. Sensitivity analysis can be performed on this pair of models to determine those parameters of the original model that are most sensitive to change and therefore require further expense in obtaining tighter specifications.
Smotherman, M.↗
Ultrahigh reliability prediction for fault-tolerant computer systems
A review and a critical evaluation of a representative class of state-of-the-art models for ultrahigh reliability prediction is presented. This evaluation naturally leads to a new model for ultrahigh reliability prediction now under development. The new model combines the flexibility and accuracy of simulation with the speed of analytic models.
Geist, R. M.↗
Decomposition in reliability analysis of fault-tolerant systems
The existing approaches to reliability modeling are briefly reviewed. An examination of the limitations of the existing approaches in modeling ultrareliable fault-tolerant systems illustrates the need to use decomposition techniques. The notion of behavioral decomposition is introduced for dealing with reliability models with a large number of states, and a series of examples is presented. The CARE (computer-aided reliability estimation) and HARP (hybrid automated reliability predictor) approaches to reliability are discussed.
Trivedi, K. S.↗
A tutorial on the CARE III approach to reliability modeling
The CARE 3 reliability model for aircraft avionics and control systems is described by utilizing a number of examples which frequently use state-of-the-art mathematical modeling techniques as a basis for their exposition. Behavioral decomposition followed by aggregration were used in an attempt to deal with reliability models with a large number of states. A comprehensive set of models of the fault-handling processes in a typical fault-tolerant system was used. These models were semi-Markov in nature, thus removing the usual restrictions of exponential holding times within the coverage model. The aggregate model is a non-homogeneous Markov chain, thus allowing the times to failure to posses Weibull-like distributions. Because of the departures from traditional models, the solution method employed is that of Kolmogorov integral equations, which are evaluated numerically.
Trivedi, K. S.↗