Article Preview
Top1. Introduction
With the rapid development of wireless communication and microelectronics technologies, a self-organized distributed sensor network called a wireless sensor network (WSN) has been widely applied for event monitoring (Othman & Shazali, 2012). A WSN is composed of a large number of low-cost micro sensor nodes, which are deployed in the monitored area. WSN nodes communicate with each other via wireless channels. They cooperatively sense, collect and process the information of sensing objects in the monitored area, and then send it to the observer (Othman & Shazali, 2012). WSNs also have a wide range of applications in battlefield surveillance, warehouse management, health care assistance, natural disaster warning, environmental monitoring, and many other domains (Borges, Velez, & Lebres, 2014).
Energy is extremely crucial to WSNs, because sensor nodes are usually powered by on-board batteries or super-capacitors. Due to the small size of sensor nodes, the battery capacity is limited. Sometimes the lifetime of WSNs cannot be prolonged by replacing their batteries because of high maintenance cost, which restricts the development and applications of WSNs (Xie et al., 2012). At present, most previous works to preserve energy resource are based on balancing power consumption (Tarng et al., 2011), mobile sensors (Butler et al., 2004; Zhou et al., 2004) and mobile collectors (Yao, Li, & Wu, 2006), using multiple collectors and other methods. However, these methods only reduce the rate of energy consumption, and cannot essentially prolong the lifetime of WSNs.
In recent years, the above energy bottleneck may be alleviated with the advance of wireless power transfer (WPT) techniques (Xie et al., 2013). WPT can be used to deliver energy and provide extra energy for WSNs. A wireless sensor network equipped with wireless charging devices is called a wireless rechargeable sensor network (WRSN) (Xie et al., 2013). Therefore, such a wireless network becomes a development platform for many future applications. It mainly includes a base station (BS), several wirelessly rechargeable wireless communication sensor nodes, and wireless charging vehicles (WCVs). The base station collects sensory data from sensor nodes and provides a quick battery replacing service for WCVs. The WCV, equipped with WPT devices, can wirelessly replenish energy for sensor nodes. At the same time, it is controlled and directed by BS. As a result, how to plan a better scheduling path of WCV for satisfying more charging requests of nodes is very important in WRSNs, especially for large scale WRSNs.
Most previous studies consider the charging path planning problem by applying deterministic or non-deterministic methods (Xu et al., 2018; Stankovic et al., 2012; Bouakaz et al., 2014). In deterministic methods, some necessary information of sensor nodes such as location coordinates and energy status are assumed to be recorded by BS in advance, then the WCV travels according to a fixed charging path periodically so that each node can obtain charging service at a certain fixed time interval. On the other hand, in non-deterministic methods, nodes actively monitor their residual energy by themselves. Nodes send out charging requests to BS when the energy levels fall below a certain threshold. The BS maintains a service pool to store the received requests and establish a charging queue (charging schedule) according to some charging discipline. Then, the WCV performs charging task according to the charging schedule. Therefore, non-deterministic methods are more flexible to the variations in energy consumptions of nodes than deterministic methods.