In wireless rechargeable sensor networks (WRSNs), most of researches address energy scarcity by introducing one or multiple ground mobile vehicles to recharge energy-hungry sensor nodes. The charging efficiency is limited by the moving speed of ground chargers and rough environments, especially in large-scale scenarios or challenging scenarios such as separate islands. To address the limitations, some researchers consider replacing ground mobile chargers with lightweight unmanned aerial vehicles (UAVs) to support extremely large-scale scenarios, because of the UAV moving at higher speed without geographical limitation. Moreover, multiple automatic landing wireless charging PADs are deployed in the network to recharge UAVs automatically. In this work, we investigate the problem of introducing the minimal number of PADs in UAV-based WRSNs. We propose a novel and adaptive PAD deployment scheme named CDC & DSC that can adapt to arbitrary locations of the base station, arbitrary geographic distributions of sensor nodes, and arbitrary sizes of network areas. In the proposed scheme, we first obtain an initial PAD deployment solution by clustering nodes in geographic locations. Then, we propose a center shift combining algorithm to optimize this solution by shifting the location of PADs and attempting to merge the adjacent PADs. The simulation results show that compared to existing algorithms, our proposed scheme can use fewer PADs to charge the whole network.
翻译:在无线再充电传感器网络(WWSNS)中,大多数研究都通过引入一台或多台地面机动车辆来补给能量饥饿传感器节点,解决能源稀缺问题。收费效率因地面充电器和粗环境的移动速度而受到限制,特别是在大型情景或具有挑战性的情形中,如单独的岛屿。为解决这些局限性,一些研究人员考虑用轻型无人驾驶飞行器(UAVs)取代地面充电充电器,以支持超大型情景,因为无人驾驶飞行器以更高速度无地理限制地移动。此外,在网络中安装了多个自动着陆无线充电 PADs,自动补给无人驾驶飞行器。在这项工作中,我们调查了在以UAV为基础的WSNSs中引入最低数量PADs的问题。我们提议了一个创新的适应性PAD部署计划,名为CD & DSC,可以适应基站的任意位置,感官节点的任意地理分布和网络的任意大小。在拟议办法中,我们首先通过将节点组合方式获得初步的PAD部署解决方案。然后,我们提议将核心算法合并为优化这一解决方案,将现有的PAD系统升级为比较的版本。