Adaptive low-overhead scheduling for periodic and reactive intermittent execution

Abstract

Batteryless energy-harvesting devices eliminate the need in batteries for deployed sensor systems, enabling longer lifetime and easier maintenance. However, such devices cannot support an event-driven execution model (e.g., periodic or reactive execution), restricting the use cases and hampering real-world deployment. Without knowing exactly how much energy can be harvested in the future, robustly scheduling periodic and reactive workloads is challenging. We introduce CatNap, an event-driven energy-harvesting system with a new programming model that asks the programmer to express a subset of the code that is time-critical. CatNap isolates and reserves energy for the time-critical code, reliably executing it on schedule while deferring execution of the rest of the code. CatNap degrades execution quality when a decrease in the incoming power renders it impossible to maintain its schedule. Our evaluation on a real energy-harvesting setup shows that CatNap works well with end-to-end, real-world deployment settings. CatNap reliably runs periodic events when a prior system misses the deadline by 7.3x and supports reactive applications with a 100% success rate when a prior work shows less than a 2% success rate.