Profit-driven UAV Green Wireless Charging for WSN

Junlong Chen, Xilong Liu
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引用次数: 1

Abstract

Wireless Sensor Network (WSN) has been widely applied in Internet of Things (IoT). WSN brings great convenience to people's daily lives. In reality, the limited battery's capacity always constrains normal function time of a wireless sensor. Replacing the batteries one by one for the wireless sensors deployed in large-scale network or in dangerous places is quite infeasible. The recent research results reveal that unmanned aerial vehicle (UAV) equipped with a point-to-point far-field wireless charging unit can efficiently facilitate remote powering for WSN. The advantage of adopting charging UAV is that the distance between the wireless energy emitter and the receiver can be shortened; thus, enhancing the wireless charging efficiency. However, a UAV's energy supply usually does not allow the long-term charging mission, hence, the cost and profit of UAV wireless charging should be considered in UAV provisioned charging service. In this work, we first build a UAV wireless charging pricing model to calculate the profit of the charging service, and then, we propose the Profit-driven UAV Charging (PUC) algorithm to maximize the UAV charging profit. Through extensive simulations, we have validated that the performance of our proposed algorithm outperforms the conventional Nearest-Job-Next with Preemption (NJNP) algorithm.
利润驱动的无人机WSN绿色无线充电
无线传感器网络(WSN)在物联网(IoT)中得到了广泛的应用。无线传感器网络给人们的日常生活带来了极大的便利。在现实中,有限的电池容量往往会限制无线传感器的正常工作时间。对于部署在大规模网络或危险场所的无线传感器,逐个更换电池是非常不可行的。最近的研究结果表明,在无人机上安装点对点远场无线充电单元可以有效地实现无线传感器网络的远程供电。采用充电无人机的优点是可以缩短无线能量发射器和接收器之间的距离;从而提高无线充电效率。然而,无人机的能量供应通常不允许长期充电任务,因此,在无人机提供充电服务时,需要考虑无人机无线充电的成本和利润。本文首先建立无人机无线充电定价模型,计算充电服务的利润,然后提出利润驱动的无人机充电(PUC)算法,实现无人机充电利润最大化。通过大量的仿真,我们已经验证了我们提出的算法的性能优于传统的具有抢占(NJNP)的Nearest-Job-Next算法。
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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