Modeling recovery time distributions in ultrareliable fault-tolerant systems

Abstract

A technique for fitting distributions to empirical recovery time data that focuses on the components that dominate system reliability is proposed. The technique uses Goldfarb's conjugate gradient descent search to minimize the L/sup 2/ norm of the error projected in the Laplace transform domain. A new parametric family of distributions is also suggested and is seen to provide uniformly better predictions of system reliability than the standard distributions used for this purpose, i.e. gamma, Weibull, and log normal. Applications to several sets of real recovery time data are provided.<>