Investigation of soft error mitigation techniques on resource-constrained IoT Edge systems.

软错误由许多影响引起，但这里主要关注的是由本地源、宇宙射线或被α发射体污染的包装材料的辐射撞击引起的软错误。无论原因如何，软错误的最终结果都是一个（或多个）位从其预期状态翻转。检测和纠正这些事件的传统方法包括三重模块冗余（或仅用于检测的双重），或者在软件中，在同一处理器上多次执行相同的代码并比较结果，或者在硬件中，多个处理器执行一次代码并比较结果。TMR是昂贵的，无论是在硬件的面积、存储器和功率方面，还是在软件的时间、存储器和功率方面。其他技术也有类似的高成本。嵌入式系统通常在其资源方面受到高度限制，并且仍然受到限制性设计要求的约束。特别是，实时系统可能无法提供执行时间的3倍增加来执行TMR，也无法提供RAM的类似增加。对于远程系统或位于无法访问位置的系统，如果使用电池，则功耗的类似增加可能需要更频繁的维修或更换。

Soft errors result from many effects, but the primary concern here is for those caused by radiation strikes from local sources, cosmic rays, or packaging materials contaminated with alpha emitters. The ultimate result of a soft error, regardless of its cause, is one (or more) bits flipped from their expected state. Traditional methods of detecting and correcting these occurrences include Triple Modular Redundancy (or Dual for detection only) either in software, executing the same code multiple times on the same processor and comparing the results, or in hardware, where multiple processors executed the code once and compare the result. TMR is costly, either in area, memory and power for hardware, or time, memory and power for software. Other techniques have similarly high costs. Embedded systems are often highly constrained in their resources and still subject to restrictive design requirements. Real-time systems, in particular, may not be able to afford a 3x increase in execution time to perform TMR, nor a similar increase in RAM. For remote systems, or those in inaccessible locations, a similar increase in power consumption may necessitate more frequent servicing or replacement if battery operated.