Component Importance Measures for Real-Time Computing Systems in the Presence of Common-Cause Failures

Component importance analysis is to measure the effect on system reliability of component reliabilities, and it can be used to the design of system from the reliability point of view. In this paper, we consider the component importance analysis of real-time computing systems in the presence of common-cause failures (CCFs) (i.e., failure dependencies). Although the CCFs are known as a risk factor of degradation of system reliability, it is difficult to evaluate the component importance measures in the presence of CCFs analytically. This paper introduces a continuous-time Markov chain (CTMC) model for real-time computing system, and applies the CTMC-based component-wise sensitivity analysis which can evaluate the component importance measures without any structure function of system. Also, in numerical experiments, we evaluate the effect of CCFs by the comparison of system performance measures and component importance in the case of system with CCFs with those in the case that there is no CCF in the system.