## 1 Introduction  
In a wireless sensor network (WSN), the amount of power provided by the battery determines whether each sensor can operate normally. Such power limitations also affect the stability of the entire WSN. To solve the problem of limited battery power, scholars have proposed studies on the design of energy-efficient routing protocols [1] and energy-harvesting wireless sensor networks (WSNs) to reduce energy consumption [2]. Neither the energy-efficient protocols nor the energy-harvesting WSNs solves the principle problem. These studies can prolong the life of WSNs. However, when the sensor exhausts the battery, the WSNs still cannot work properly. Some might argue that WSNs using solar energy can solve the problem of battery exhaustion. However, solar energy-based sensors are affected by environmental factors, and the efficiency of WSNs is significantly affected by different environments. In recent years, some researchers have proposed wireless charging technology, which can solve the problem of sensor battery power limitation, thus fundamentally solving the WSN lifetime problem [3]. The power can be transmitted using wireless chargers to RFIDs [4], sensors [5] and other terminal devices. TechNavio's market research shows that wireless charging technology has great market potential, and the 2020 global annual increase in the wireless charging market is more than 33% [6]. Due to the convenience and continuous development of wireless charging technology, wireless charging has drawn the attention of both industry and academia, especially in the realm of WSN research. The adoption of wireless charging technology to improve the survival time of WSNs has been extensively surveyed. The new type of WSN that allows wireless chargers to extend the lifetime of wireless sensors is called wireless rechargeable sensor networks (WRSNs). The main consideration for the deployment of wireless chargers in WSNs is to maintain a stable power supply for the sensors so that the sensors can perform sensing tasks in the sensing area. Based on cost considerations, the number of wireless chargers in this deployment area should be minimized. However, because the power supply of the sensors has a significant impact on the performance of the WSNs, this study attempts to find a deployment strategy that can effectively reduce the number of wireless chargers while maximizing the charging capacity. Several studies related to the deployment of wireless chargers in WRSNs have been proposed in recent years. However, these studies have some limitations, such as the grid partition that does not fit to the real environment in which the charger can be placed. Some might unrealistically assume that the data collection node or sink node does not exist. The data collection node or sink node in WSNs or WRSNs is a critical device. The sensors collect and route data to a data collection or sink node. If a sensor is near the data collection or sink node, it will bear frequent data forwarding and consume more energy. Therefore, to address the limitations of previous research, this study explores the deployment of directional chargers in a given network. In this study, the influence of data collection or sink nodes is evaluated. Previous studies have failed to address this influence. We also deal with two different types of chargers: omnidirectional and directional chargers in WRSNs. In this study, a two-stage strategy called search most and remove useless (SMRU) is proposed. In the first stage, the candidate position of the directional charger is selected on a sensor randomly. Next, we search for the number of sensors covered by the chargeable radius at the candidate position of the directional charger. The deployment given by the proposed SMRU strategy can effectively reduce the required number of directional chargers and preserve good charging utility. The experimental results demonstrate that our proposed SMRU approach outperforms previous works. The three main contributions of the proposed SMRU algorithm are as follows:  
1.