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Energy harvesting offers an attractive and promising mechanism to powerlow-energy devices. However, it alone is insufficient to enable anenergy-neutral operation, which can eliminate tedious battery charging andreplacement requirements. Achieving an energy-neutral operation is challengingsince the uncertainties in harvested energy undermine the quality of servicerequirements. To address this challenge, we present a runtime energy-allocationframework that optimizes the utility of the target device under energyconstraints using a rollout algorithm, which is a sequential approach to solvedynamic optimization problems. The proposed framework uses an efficientiterative algorithm to compute initial energy allocations at the beginning of aday. The initial allocations are then corrected at every interval to compensatefor the deviations from the expected energy harvesting pattern. We evaluatethis framework using solar and motion energy harvesting modalities and AmericanTime Use Survey data from 4772 different users. Compared to prior techniques,the proposed framework achieves up to 35% higher utility even underenergy-limited scenarios. Moreover, measurements on a wearable device prototypeshow that the proposed framework has 1000x smaller energy overhead thaniterative approaches with a negligible loss in utility.

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