ECO: Enabling Energy-Neutral IoT Devices through Runtime Allocation of Harvested Energy

TL;DR

This paper introduces a runtime energy-allocation framework for energy-harvesting IoT devices that optimizes utility and achieves near energy-neutral operation despite harvesting uncertainties, using a rollout algorithm.

Contribution

It presents a novel dynamic optimization framework with an efficient iterative algorithm for real-time energy allocation in energy-harvesting IoT devices.

Findings

Up to 35% higher utility compared to prior methods.

Achieves energy-neutral operation with solar and motion energy sources.

Prototype implementation shows 1000x smaller energy overhead.

Abstract

Energy harvesting offers an attractive and promising mechanism to power low-energy devices. However, it alone is insufficient to enable an energy-neutral operation, which can eliminate tedious battery charging and replacement requirements. Achieving an energy-neutral operation is challenging since the uncertainties in harvested energy undermine the quality of service requirements. To address this challenge, we present a runtime energy-allocation framework that optimizes the utility of the target device under energy constraints using a rollout algorithm, which is a sequential approach to solve dynamic optimization problems. The proposed framework uses an efficient iterative algorithm to compute initial energy allocations at the beginning of a day. The initial allocations are then corrected at every interval to compensate for the deviations from the expected energy harvesting pattern. We evaluate this framework using solar and motion energy harvesting modalities and American Time Use Survey data from 4772 different users. Compared to prior techniques, the proposed framework achieves up to 35% higher utility even under energy-limited scenarios. Moreover, measurements on a wearable device prototype show that the proposed framework has 1000x smaller energy overhead than iterative approaches with a negligible loss in utility.