Improving charging efficiency with workload scheduling in energy harvesting embedded systems

Yukan Zhang, Yang Ge, Qinru Qiu
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引用次数: 12

Abstract

In energy harvesting embedded systems, if the harvested power is sufficient for the workload, extra power will be stored in the electrical energy storage (EES) bank. How much energy can be stored is affected by many factors including the efficiency of the energy harvesting module, the input/output voltage of the DC-DC converters, the status of the EES elements, and the characteristics of the workload. This paper investigates the impact of workload scheduling of the embedded system on the storage efficiency of the EES bank. We first provide an approximated but accurate power consumption model of the DC-DC converter. Based on this model, we analytically prove that an optimal workload schedule is to always execute high power task first. Experimental results confirm that proposed scheduling strategy outperforms all other possible scheduling and increases the amount of stored energy by up to 10.41% in average.
利用工作负载调度提高能量收集嵌入式系统的充电效率
在能量收集嵌入式系统中,如果收集的功率足以满足工作负载,则多余的功率将存储在电能存储库中。可以存储多少能量受到许多因素的影响,包括能量收集模块的效率、DC-DC转换器的输入/输出电压、EES元件的状态以及工作负载的特性。本文研究了嵌入式系统的工作负载调度对EES银行存储效率的影响。我们首先提供了一个近似但准确的DC-DC转换器的功耗模型。在此模型的基础上,分析证明了最优的工作负载调度是优先执行高功率任务。实验结果表明,该调度策略优于所有其他调度策略,平均可提高10.41%的储能量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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