利用移动充电器为路由不对称 WRSN 进行定向 WPT 充电

Zhenguo Gao, Qi Zhang, Qingyu Gao, Yunlong Zhao, Hsiao-Chun Wu
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引用次数: 0

摘要

无线充电传感器网络(WRSN)中无线充电节点的移动充电调度是一个前景广阔但仍在不断发展的研究领域。现有研究大多假定环境是对称的,两个地点之间相反方向的路由成本被认为是相同的。然而,在实际环境中,地形限制、风或水流等各种因素都可能使路由对称假设失效,从而大大限制了这些解决方案在路由不对称无线传感器网络(RA-WRSN)中的性能。为了解决 WRSN 移动充电调度中的路由不对称难题,本文系统地研究了非对称定向移动充电器(DMC)充电调度(ADMCCS)的基本问题,目的是在满足网络节点充电需求的同时最大限度地减少能量损耗。之所以假设 DMC 模型,是因为其结果很容易应用于全向移动充电器 (OMC) 的特殊情况。为了解决 ADMCCS 问题,我们提出了一个四步框架。首先,利用我们设计的基于 K-means 的充电位置生成(KCPG)算法,选择最小尺寸的高效充电位置集,以解决充电位置选择空间无限的难题;接着,利用最优算法确定这些位置上的最小尺寸功能等效方向集,以解决充电方向无限的难题。随后,通过提出并求解一个非线性程序(NLP)问题,得到这些位置上所有方向的最佳能量传输时间长度。最后,对非对称旅行推销员问题的 Lin-Kernighan 启发式(LKH)算法进行了调整,以获得高概率的最优环路巡回,从而解决路由不对称的难题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Directional WPT Charging for Routing-Asymmetric WRSNs with a Mobile Charger
Mobile Charge Scheduling for wirelessly charging nodes in Wireless Rechargeable Sensor Networks (WRSNs) is a promising but still evolving research area. Existing research mostly assumes a symmetric environment, where the routing costs in opposite directions between two locations are considered identical. However, various factors such as terrain restrictions and wind or water flows may invalidate the routing-symmetric assumption in practical environments, thereby significantly limiting the performance of these solutions in routing-asymmetric WRSNs (RA-WRSNs). To address the routing-asymmetric challenges in mobile charge scheduling for WRSNs, this paper systematically investigates the underlying Asymmetric Directional Mobile Charger (DMC) Charge Scheduling (ADMCCS) problem, aiming to minimize energy loss while satisfying the charging demands of the network nodes. The DMC model is assumed because its results can be easily applied to the specialized case of an Omnidirectional Mobile Charger (OMC). To solve the ADMCCS problem, we propose a four-step framework. First, a minimum-size efficient charging position set is selected using our designed K-means-based Charging Position Generation (KCPG) algorithm, addressing the challenge of the unlimited charging position selection space. Next, minimum-size functional-equivalent direction sets at these positions are determined using an optimal algorithm, tackling the challenge of infinite charging directions. Subsequently, the optimal energy transmission time lengths for all directions at the positions are obtained by formulating and solving a Nonlinear Program (NLP) problem. Finally, the Lin-Kernighan Heuristic (LKH) algorithm for the Asymmetric Traveling Salesman Problem is adapted to obtain a highly probable optimal loop tour, addressing the routing-asymmetric challenge.
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