Abstract
Abstract 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.
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