Charge-Aware Duty Cycling Methods for Wireless Systems under Energy Harvesting Heterogeneity

Abstract

Recent works have designed systems containing tiny devices to communicate with harvested ambient energy, such as the ambient backscatter and renewable sensor networks. These systems often encounter the heterogeneity and randomness of ambient energy. Meanwhile, the energy storage unit, such as the battery or capacitor, has the inherent property of imperfect charge efficiency λ (λ ≤ 1), which is usually low when the power of the ambient energy is weak or variable. These features bring new challenges in using the harvested energy efficiently. This article calls it the stochastic duty cycling problem and studies it under three cases—offline, online, and correlated stochastic duty cycling—to maximize utilization efficiency. We design an offline algorithm 1 for the offline case with optimal performance. An approximation algorithm with the ratio 1 − e −γ is designed for the online case. By adding initial negotiation among devices, we present a correlated algorithm and prove its approximation ratio theoretically. Experiment evaluation on our real energy harvesting platform shows that the offline algorithm performs over the other two algorithms. The correlated algorithm may not perform over the online one under the impacts of the three metrics: heterogeneity, charge efficiency, and energy harvesting probability.