Low-power small-scale embedded sensing systems employing batteries generally impose high maintenance costs. To enable maintenance-free operation, they are powered from energy harvested from the environment thus making them batteryless. However, due to high variance of ambient energy, these batteryless embedded devices are unable to harvest enough energy from the environment required for continuous device operation thus hampering application progress and causing frequent loss of volatile program-state. Therefore, these batteryless devices have to employ state retention mechanisms to save the volatile program-state to non-volatile storage before interruption. These batteryless embedded sensing devices are known as transiently-powered systems (TPS). In this article, we survey existing literature to identify strategies and techniques used by each existing literature to decide what amount of volatile program-state needs to be saved and when to save it. We list the challenges in retaining program-state across periods of energy unavailability and how existing state-of-the-art solutions tackle them. We also describe different memory models and discuss factors governing the choice of each model for TPS deployment.

采用电池的低功率小型嵌入式传感系统通常会带来较高的维护成本。为了实现免维护运行，它们使用从环境中收集的能量来供电，因此无需电池。但是，由于环境能量的高变化，这些无电池嵌入式设备无法从连续设备运行所需的环境中获取足够的能量，从而阻碍了应用程序的进展并导致易失性编程状态的频繁丢失。因此，这些无电池设备必须采用状态保持机制，以在中断之前将易失性程序状态保存到非易失性存储器中。这些无电池嵌入式传感设备被称为瞬态供电系统（TPS）。在这篇文章中，我们调查现有的文献，以确定由每个现有的文献来决定策略和技巧，有什么要保存的挥发性程序状态的需求数量和时保存它。我们列出了在能源不可用期间保持计划状态的挑战，以及现有的最新解决方案如何解决这些挑战。我们还将描述不同的内存模型，并讨论控制TPS部署的每种模型选择的因素。