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Load-matching adaptive task scheduling for energy efficiency in energy harvesting real-time embedded systems

机译:负载匹配自适应任务调度,用于在能量收集实时嵌入式系统中提高能效

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In this paper we present a load matching task scheduling algorithm for energy harvesting real-time embedded systems using a realistic model for the battery charging and discharging processes. The proposed approach addresses two important issues that have not been considered by previous work: load matching and battery charge/discharge overhead. The new algorithm increases available energy by managing the system load through task scheduling so that the energy harvesting module delivers maximum power output. It further improves the system wide energy efficiency by considering the charging and discharging overhead when deciding if the harvested energy should be used to charge the battery or directly on the circuits. Experimental results show that, comparing to the best of the existing techniques the proposed algorithm improves the system wide energy efficiency by 8.0% to 56.3% and reduces deadline misses by 13.3% to 81.8% under different workload conditions.
机译:在本文中,我们提出了一种负载匹配任务调度算法,该算法使用电池充电和放电过程的逼真的模型来收集实时嵌入式系统的能量。所提出的方法解决了先前工作未曾考虑的两个重要问题:负载匹配和电池充电/放电开销。新算法通过任务调度来管理系统负载,从而增加了可用能量,从而使能量收集模块能够提供最大的功率输出。在决定是将采集的能量用于电池充电还是直接在电路上充电时,通过考虑充电和放电开销,可以进一步提高系统的能源效率。实验结果表明,与现有技术中的最佳技术相比,该算法在不同工作量条件下将系统范围的能源效率提高了8.0%至56.3%,并将最后期限遗漏减少了13.3%至81.8%。

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