嵌入式系统中老化检测与监控技术综述
A Review of Techniques for Ageing Detection and Monitoring on Embedded Systems
AI总结：
本文综述嵌入式系统中COTS组件的硬件老化检测与监控技术，涵盖核心老化机制、技术工作原理分类，发现FPGAs在线技术应用更广泛及机器学习应用趋势，并指出研究机会以促进未来研究。
摘要：
嵌入式数字设备正逐步部署于可靠或安全关键系统中。这些设备会经历显著的硬件老化，尤其在恶劣环境下，这增加了其故障概率。理解老化过程并早期检测硬件退化对保障系统可靠性至关重要。本综述回顾了核心老化机制，识别并分类了嵌入式系统中普遍存在的商用现货（COTS）组件（现场可编程门阵列（FPGAs）、微控制器、片上系统（SoCs）及其电源）的老化检测与监控技术的通用工作原理。从综述中发现，在线技术在FPGAs上的应用比在其他组件上更广泛，且机器学习应用于硬件老化分析的趋势正在上升。基于所综述的文献，我们识别了该领域的研究机会和潜在方向。通过这项工作，我们旨在以简洁的方式系统地呈现所有主要方法，以促进未来研究。
英文摘要：
Embedded digital devices are progressively deployed in dependable or safety-critical systems. These devices undergo significant hardware ageing, particularly in harsh environments. This increases their likelihood of failure. It is crucial to understand ageing processes and to detect hardware degradation early for guaranteeing system dependability. In this survey, we review the core ageing mechanisms, identify and categorize general working principles of ageing detection and monitoring techniques for Commercial-Off-The-Shelf (COTS) components that are prevalent in embedded systems: Field Programmable Gate Arrays (FPGAs), microcontrollers, System-on-Chips (SoCs), and their power supplies. From our review, we find that online techniques are more widely applied on FPGAs than on other components, and see a rising trend towards machine learning application for analysing hardware ageing. Based on the reviewed literature, we identify research opportunities and potential directions of interest in the field. With this work, we intend to facilitate future research by systematically presenting all main approaches in a concise way.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
