Evaluation of A Resilience Embedded System Using Probabilistic Model-Checking

TL;DR

This paper uses probabilistic model checking to evaluate a new resilience strategy for embedded systems, demonstrating its effectiveness in reducing failures and downtime in MPU operations.

Contribution

It introduces a novel evaluation method for resilience strategies in embedded systems using probabilistic model checking, combining qualitative and quantitative analysis.

Findings

Resilience strategy significantly reduces system failures.

Evaluation method is cost-effective and reliable.

Demonstrates benefits of the resilience approach.

Abstract

If a Micro Processor Unit (MPU) receives an external electric signal as noise, the system function will freeze or malfunction easily. A new resilience strategy is implemented in order to reset the MPU automatically and stop the MPU from freezing or malfunctioning. The technique is useful for embedded systems which work in non-human environments. However, evaluating resilience strategies is difficult because their effectiveness depends on numerous, complex, interacting factors. In this paper, we use probabilistic model checking to evaluate the embedded systems installed with the above mentioned new resilience strategy. Qualitative evaluations are implemented with 6 PCTL formulas, and quantitative evaluations use two kinds of evaluation. One is system failure reduction, and the other is ADT (Average Down Time), the industry standard. Our work demonstrates the benefits brought by the resilience strategy. Experimental results indicate that our evaluation is cost-effective and reliable.