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Geometric Analysis of Energy Saving for Directional Charging in WRSNs

机译:逆潮中定向充电节能几何分析

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Wireless power transfer (WPT) enables a reliable and convenient charging paradigm. This article concerns the fundamental issue of energy saving in wireless rechargeable sensor networks (WRSNs), i.e., given a fixed number of rechargeable sensors (RSs) with their locations and charging demands, we focus on a minimal charging expenditure (MAP) problem with directional WPT to decrease the energy expenditure of the charger, on condition that the charging demands of all sensors are satisfied. In particular, we consider the anisotropic energy receiving property of RSs, which is closely related to the distance and the angle between the sensor and the charger antenna's orientation in directional WPT. We transform the MAP problem into an optimal function placement (OFA) problem, which can be geometrically analyzed in a rectangular coordinate system and is NP-hard. First, we study the OFA problem in the case of uniformly distributed sensors with identical charging demands, we develop the uniform charging strategy (UCS) to bound the total charging expenditure as Theta(1) for any number of sensors N. Based on the acquired insights, we further studied the OFA problem when the distribution of charging demands is Gaussian. We bound the total charging expenditure as Theta(1) for any number of sensors N, by developing the layered charging strategy (LCS). Extensive simulation results confirmed the performance of our design compared with two baseline algorithms. Both of the theoretical and simulations results reveal that the total energy expenditure of the charger is strongly related to the sensors' charging demands, however, is less affected by the number of sensors in the network.
机译:无线电源传输(WPT)可实现可靠且方便的充电范例。本文涉及无线可充电传感器网络(WRSNS)中节能的基本问题,即,给定与其位置和充电需求的固定数量的可充电传感器(RSS),我们专注于具有定向的最小充电支出(MAP)问题为了减少充电器的能源支出,根据所有传感器的充电需求满足的条件。特别是,我们考虑RSS的各向异性能量接收性能,其与传感器和充电器天线在定向WPT之间的距离和充电器天线的方向密切相关。我们将地图问题转换为最佳函数放置(OFA)问题,可以在矩形坐标系中几何分析,并且是NP-HARD。首先,我们在具有相同充电需求的均匀分布式传感器的情况下研究OFA问题,我们开发统一的充电策略(UCS)将总收费支出与任何数量的传感器N.基于所获取的洞察力,当充电需求的分配是高斯时,我们进一步研究了OFA问题。通过开发分层充电策略(LCS),我们将总收费支出与任何数量的传感器N相结合(1)。广泛的仿真结果证实了我们设计的性能与两个基线算法相比。两个理论和模拟结果表明,充电器的总能量消耗与传感器的充电需求强烈相关,但是,受网络中传感器数量的影响较小。

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