Intermittent computing (ImC) refers to the scenario where periods of program execution are separated by reboots. ImC systems are generally powered by energy-harvesting (EH) devices: they start executing a program when the accumulated energy reaches a threshold and stop when the energy buffer is exhausted. Since ImC does not depend on a fixed supply of power, it can be used in a wide range of scenarios/devices such as medical implants, wearables, IoT sensors, extraterrestrial systems and so on. Although attractive, ImC also brings challenges such as avoiding data-loss and data inconsistency, and striking the right balance between performance, energy and quality of the result. In this paper, we present a survey of techniques and systems for ImC. We organize the works on key metrics to expose their similarities and differences. This paper will equip researchers with the knowledge of recent developments in ImC and also motivate them to address the remaining challenges for reaping the full potential of ImC.

间歇计算（ImC）指的是程序执行的时间间隔由重新启动分隔的情况。ImC系统通常由能量收集（EH）设备供电：它们在累积的能量达到阈值时开始执行程序，并在能量缓冲器耗尽时停止执行程序。由于ImC并不依赖固定的电源，因此它可用于各种场景/设备，例如医疗植入物，可穿戴设备，IoT传感器，地外系统等。尽管具有吸引力，但ImC还带来了诸如避免数据丢失和数据不一致以及在性能，能量和结果质量之间寻求适当平衡之间的挑战。在本文中，我们对ImC的技术和系统进行了概述。我们根据关键指标组织作品，以揭示它们的异同。