A dynamic programming schedule trading off quality and stability in task allocation for energy-neutral Internet of Things devices harvesting solar energy

Abstract

Energy neutrality in an energy harvesting Internet of Things (IoT) device ensures continuous operation of the device by trading performance with energy consumption, and a way to achieve this is by adopting a task-based model. In this model, the device embeds several alternative tasks with different ratio energy-cost/quality and a scheduler that, depending on the current energy production and battery level, runs at any time the best task to maximize the performance while guaranteeing energy neutrality. In this context, this work proposes a novel scheduling algorithm that takes into account also the stability of the device, by minimizing the leaps of quality between two consecutive tasks in the scheduling. We show by simulation and by experiments on a low-power IoT platform that the proposed algorithm greatly improves the stability of the device with respect to the state-of-the-art algorithms, with a marginal worsening of the overall quality of the tasks executed.