PES: An Energy and Throughput Model for Energy Harvesting IoT Systems

Abstract

The Internet of Things (IoT) requires ultra-low-power sensor platforms that can be deployed at scale. Scalable systems however cannot be battery-powered because replacing batteries at scale is costly, impractical and has a negative impact on the environment. The key alternative is to rely on energy harvesting, but this is challenging because the developer needs to ensure that the application achieves sufficient throughput, i.e., the sensor platform delivers information to the back-end system at a sufficient rate when provided with a certain amount of energy. We hence propose the analytical Periodic Energy Harvesting Systems (PES) model which enables developers to explore energy versus throughput trade-offs early in the design process – thereby enabling developers to select a reasonable ultralow-power platform and energy harvesting technology before incurring the (significant)) overhead of adapting their application to the particularities of the platform. PES faithfully models the energy consumed by an IoT application during sampling and communication as well as while idle between samples. If the average power output of the energy harvesting subsystem is insufficient to sustain the application, PES uses the mismatch to predict the number of shutdowns required to harvest sufficient energy. PES achieves an average error of 3.6% across the IoT applications we consider in this work; a significant improvement over the 87.3% average error of state-of-the art EH.