Ageing Monitoring for Commercial Microcontrollers Based on Timing Windows

2026-01-05

arXiv.org

AI Summary

This work addresses the vulnerability of commercial microcontrollers in high-reliability embedded systems to timing errors induced by hardware aging, a challenge inadequately mitigated by conventional static guardbanding approaches that sacrifice performance and lack dynamic early-warning capabilities. To overcome these limitations, the paper proposes a lightweight, hardware-free, field-deployable software self-testing mechanism that dynamically monitors aging effects through variable-length timing windows and continuously estimates shifts in the maximum operating frequency. Experimental validation on real hardware demonstrates that the method accurately detects a 13.79% reduction in maximum operating frequency under a 60°C temperature increase, confirming its effectiveness, consistency, and practical utility. This approach successfully transcends the constraints of static guardbanding while enabling real-time aging awareness without additional hardware overhead.

Technology Category

• Machine Learning: Hardware-aware ML
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Multiagent Systems: Multiagent Systems under Uncertainty

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Microcontrollers are increasingly present in embedded deployments and dependable applications, for which malfunctions due to hardware ageing can have severe impact. The lack of deployable techniques for ageing monitoring on these devices has spread the application of guard bands to prevent timing errors due to degradation. Applying this static technique can limit performance and lead to sudden failures as devices age. In this paper, we follow a software-based self-testing approach to design monitoring of hardware degradation for microcontrollers. Deployable in the field, our technique leverages timing windows of variable lengths to determine the maximum operational frequency of the devices. We empirically validate the method on real hardware and find that it consistently detects temperature-induced degradations in maximum operating frequency of up to 13.79 % across devices for 60 {\deg}C temperature increase.

Problem

• ageing monitoring
• microcontrollers
• hardware degradation
• timing errors
• dependable applications

Innovation

• ageing monitoring
• timing windows
• software-based self-testing
• microcontroller reliability
• maximum operational frequency