The effects of energy management on reliability in real-time embedded systems

TLDR

Real‑time systems can use slack time for recovery and frequency/voltage scaling for energy savings, but fault rates also rise with higher frequency and voltage, creating a trade‑off between reliability and energy consumption. The study investigates how frequency and voltage scaling affect fault rates, proposes two new fault‑rate models based on prior data, and then examines the impact of energy management on system reliability. The authors model fault rates using two new models derived from existing data and analyze how frequency and voltage scaling influence reliability. Analysis indicates that frequency and voltage scaling can dramatically reduce reliability, and neglecting their effect on fault rates leads to overly optimistic reliability estimates.

Abstract

The slack time in real-time systems can be used by recovery schemes to increase system reliability as well as by frequency and voltage scaling techniques to save energy. Moreover, the rate of transient faults (i.e., soft errors caused, for example, by cosmic ray radiations) also depends on system operating frequency and supply voltage. Thus, there is an interesting trade-off between system reliability and energy consumption. This work first investigates the effects of frequency and voltage scaling on the fault rate and proposes two fault rate models based on previously published data. Then, the effects of energy management on reliability are studied. Our analysis results show that, energy management through frequency and voltage scaling could dramatically reduce system reliability, and ignoring the effects of energy management on the fault rate is too optimistic and may lead to unsatisfied system reliability.