Quantification of effects of degraded hardware on the execution of self-healing software using Continuous Time Markov Chain and Reliability

Abstract

Embedded systems and Systems on Chips (SoC) are widely used in many applications. The tasks are to be executed in a time-bound manner for critical applications. The latency and worst-case delays shall not exceed the acceptable limits. These systems are designed using software/firmware and hardware components that are tightly coupled. The state of hardware and software/firmware plays a major role in determining the performance and dependability of the system. This paper studies the effects of the degraded state of the hardware on the execution of self-healing software and the system. While hardware and software design teams aim to ensure predictability, it is impossible to guarantee it completely due to the randomness of hardware failure events and resident errors in software. Usage of the system for safety critical systems requires these uncertainties to be quantified for design assurance and certification. Therefore, we propose a Continuous Time Markov Chain (CTMC) based approach to characterize the effects of degraded hardware on software execution. Reliability, which is one of the dependability metrics, is also quantified. The proposed approach is validated using data collected from one of the software-intensive complex hardware equipment of a fighter aircraft.