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Prediction free energy neutral power management for energy harvesting wireless sensor nodes

机译:能量收集无线传感器节点的预测自由能量中性功率管理

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Current power management mechanisms for energy harvesting wireless sensors typically rely on predicted information about the amount of energy that can be harvested in the future. However, such mechanisms suffer from inevitable prediction errors, which in turn degrade the overall performance in real implementations. To circumvent such problems, we propose a fundamental framework to efficiently manage the harvested energy in a prediction free manner. In particular, we theoretically derive a set of Budget Assigning Principles (BAPs) to maximize the amount of harvested energy that Can be utilized by a sensor in the presence of battery energy storage inefficiencies, which in turn maximize the sensor's performance level in terms of the sensor's average duty cycle. A Prediction FREE Energy Neutral (P-FREEN) power management mechanism is then proposed to implement the BAPs based solely on current observed energy harvesting rate and battery residual energy level. The performance of P-FREEN is verified via theoretical analysis and extensive computer simulations using real life energy harvesting data sets. (C) 2013 Elsevier B.V. All rights reserved.
机译:用于能量收集无线传感器的当前功率管理机制通常依赖于有关将来可以收集的能量数量的预测信息。然而,这样的机制遭受不可避免的预测误差,这反过来会降低实际实现中的整体性能。为了避免此类问题,我们提出了一个基本框架,以一种无预测的方式有效地管理所收集的能量。特别是,我们从理论上推导了一套预算分配原则(BAP),以在电池能量存储效率低下使传感器可以利用的收集能量最大化,从而又就传感器性能而言最大化传感器的性能水平。传感器的平均占空比。然后,提出了一种免费的无预测能量(P-FREEN)电源管理机制,以仅基于当前观察到的能量收集速率和电池剩余能量水平来实施BAP。通过使用现实生活中的能量收集数据集进行的理论分析和广泛的计算机模拟,可以验证P-FREEN的性能。 (C)2013 Elsevier B.V.保留所有权利。

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