The localization of sensor nodes is a significant issue in wireless sensor networks (WSNs) because many applications cannot provide services without geolocation data, especially during disaster management. In recent years, a promising unknown-nodes positioning method has been developed that localizes unknown nodes, employing a GPS-enabled mobile anchor node moving in the network, and broadcasting its location information periodically to assist localization. In contrast to most studies on path planning that assume infinite energy of the mobile anchor node, the anchor node in this study, consumes different amounts of energy during phases of startup, turning, and uniform motion considering the aftermath of disasters. To enable a trade-off between location accuracy and energy consumption, a path-planning algorithm combining a Localization algorithm with a Mobile Anchor node based on Trilateration (LMAT) and SCAN algorithm (SLMAT) is proposed. SLMAT ensures that each unknown node is covered by a regular triangle formed by beacons. Furthermore, the number of corners along the planned path is reduced to save the energy of the mobile anchor node. In addition, a series of experiments have been conducted to evaluate the performance of the SLMAT algorithm. Simulation results indicate that SLMAT outperforms SCAN, LMAT, HILBERT, and Z-curve in terms of localization accuracy and energy consumption.

中文翻译：

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无线传感器网络中基于移动锚节点定位的灾害管理导向路径规划

传感器节点的定位是无线传感器网络 (WSN) 中的一个重要问题，因为许多应用程序在没有地理定位数据的情况下无法提供服务，尤其是在灾难管理期间。近年来，一种有前途的未知节点定位方法被开发出来，它定位未知节点，采用在网络中移动的支持 GPS 的移动锚节点，并定期广播其位置信息以辅助定位。与大多数假设移动锚节点能量无限的路径规划研究相比，本研究中的锚节点在考虑到灾难后果的启动、转弯和匀速运动阶段消耗不同量的能量。为了实现定位精度和能耗之间的权衡，提出了一种基于三边测量(LMAT)和扫描算法(SLMAT)的定位算法与移动锚节点相结合的路径规划算法。SLMAT 确保每个未知节点都被信标形成的正三角形覆盖。此外，减少了沿规划路径的拐角数量，以节省移动锚节点的能量。此外，还进行了一系列实验来评估 SLMAT 算法的性能。仿真结果表明，SLMAT 在定位精度和能耗方面优于 SCAN、LMAT、HILBERT 和 Z-curve。减少沿规划路径的拐角数量，以节省移动锚节点的能量。此外，还进行了一系列实验来评估 SLMAT 算法的性能。仿真结果表明，SLMAT 在定位精度和能耗方面优于 SCAN、LMAT、HILBERT 和 Z-curve。减少沿规划路径的拐角数量，以节省移动锚节点的能量。此外，还进行了一系列实验来评估 SLMAT 算法的性能。仿真结果表明，SLMAT 在定位精度和能耗方面优于 SCAN、LMAT、HILBERT 和 Z-curve。