On Wireless Charging for Mobile Sensors

IF 5.3 2区 计算机科学 Q1 TELECOMMUNICATIONS IEEE Transactions on Green Communications and Networking Pub Date : 2024-01-31 DOI:10.1109/TGCN.2024.3360472
Rihito Tsuchida;Kazuya Sakai;Min-Te Sun;Wei-Shinn Ku
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Abstract

Battery-powered sensor devices have been an essential component in Internet of Things (IoT) applications. Much effort has been devoted to designing algorithms that identify efficient routes for a mobile wireless charger to feed sensor devices with energy without plugs, in which power is wirelessely transferred from the charger to sensors. However, existing studies assume static sensors. In this paper, we address the problem of finding better mobile charger trajectories for mobile sensors, where sensor devices are assumed to be mobile. We first introduce two problems. One is the MaxAC problem that maximizes the amount of charge from a charger to sensors within a given time constraint; the other is the MinCD problem that minimizes the charging delay to provide all the sensors with at least a target power level. To this end, we design the charging utility prediction model to estimate how much power can be transferred during a given time interval. Then, two trajectory planning algorithms are proposed, namely TPA-MaxAC and TPA-MinCD, for each problem. The simulation results demonstrate that the proposed algorithms outperform a baseline algorithm as well as the state-of-the-art wireless charging algorithms.
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关于移动传感器的无线充电
电池供电的传感器设备一直是物联网(IoT)应用的重要组成部分。人们一直致力于设计算法,以确定移动无线充电器为传感器设备提供能量的有效路径,而无需插头,在这种情况下,电能通过无线方式从充电器传输到传感器。然而,现有研究都假定传感器是静态的。在本文中,我们要解决的问题是为移动传感器找到更好的移动充电器轨迹,其中传感器设备被假定为移动的。我们首先介绍两个问题。一个是 MaxAC 问题,即在给定的时间限制内,最大化从充电器到传感器的充电量;另一个是 MinCD 问题,即最小化充电延迟,至少为所有传感器提供目标功率水平。为此,我们设计了充电效用预测模型,以估算在给定时间间隔内可以传输多少电量。然后,针对每个问题提出了两种轨迹规划算法,即 TPA-MaxAC 和 TPA-MinCD。仿真结果表明,所提出的算法优于基准算法和最先进的无线充电算法。
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来源期刊
IEEE Transactions on Green Communications and Networking
IEEE Transactions on Green Communications and Networking Computer Science-Computer Networks and Communications
CiteScore
9.30
自引率
6.20%
发文量
181
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