高级检索
    李洪峻 卜彦龙 薛 晗 李 迅 马宏绪. 面向无线传感器网络节点定位的移动锚节点路径规划[J]. 计算机研究与发展, 2009, 46(1): 129-136.
    引用本文: 李洪峻 卜彦龙 薛 晗 李 迅 马宏绪. 面向无线传感器网络节点定位的移动锚节点路径规划[J]. 计算机研究与发展, 2009, 46(1): 129-136.
    Li Hongjun, Bu Yanlong, Xue Han, Li Xun, and Ma Hongxu. Path Planning for Mobile Anchor Node in Localization for Wireless Sensor Networks[J]. Journal of Computer Research and Development, 2009, 46(1): 129-136.
    Citation: Li Hongjun, Bu Yanlong, Xue Han, Li Xun, and Ma Hongxu. Path Planning for Mobile Anchor Node in Localization for Wireless Sensor Networks[J]. Journal of Computer Research and Development, 2009, 46(1): 129-136.

    面向无线传感器网络节点定位的移动锚节点路径规划

    Path Planning for Mobile Anchor Node in Localization for Wireless Sensor Networks

    • 摘要: 节点定位是无线传感器网络技术研究的一个基本问题,大多数无线传感器网络的应用和中间件技术都需要节点的位置信息.目前比较实用的定位方法是利用一些移动锚节点(如安装有GPS)根据有效的规划路径移动,通过发送包含其自身坐标的信息来定位其他节点,该方法不过多地增加无线传感器网络成本,还可以获得较高的定位精度.在该方法中,移动锚节点的路径规划问题是需要解决的基本问题.主要研究移动锚节点的路径规划问题,把图论引入到无线传感器网络节点定位系统.把无线传感器网络看成一个连通的节点无向图,路径规划问题转化为图的生成树及遍历问题,提出了宽度优先和回溯式贪婪算法.仿真实验和真实系统实验结果表明,该方法能够很好地适应无线传感器网络节点随机分布的节点定位,可以取得较高的定位精度.

       

      Abstract: Localization is a key technology in wireless sensor networks (WSN). Many applications and middleware of WSN require the sensor nodes to obtain their locations. The accuracy of collected data can significantly be affected by an imprecise positioning of the event of interest. The main idea in most localization methods has been that some nodes with known coordinates (e.g., GPS-equipped nodes) transmit beacons with their coordinates in order to help other nodes to localize themselves. In this case, a fundamental research issue is the planning of the path that the mobile anchor should travel along. In this paper the authors study the path planning of the mobile anchor in localization for wireless sensor networks. Considering the graph theory, wireless sensor network is regarded as a connected undirected graph and then the path planning problem is translated into having a spanning tree and traversing graph. Breadth-first (BRF) and backtracking greedy (BTG) algorithms for spanning tree are proposed. The differences in performance between the two algorithms are analyzed. The BRF and BTG algorithms are effective and realistic algorithms that work in actual implementation. The simulations and real experiments show that these algorithms obtain higher localization precision and are robust in localization for the randomly deployment of the sensor nodes.

       

    /

    返回文章
    返回