Wireless Localization Using Self-Organizing Maps
Wireless Localization Using Self-Organizing Maps
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DOI：
10.1145/1236360.1236399
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发表时间：
2007-04
期刊：
影响因子：
--
通讯作者：
G. Giorgetti;S. Gupta;G. Manes
中科院分区：
文献类型：
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作者：
G. Giorgetti;S. Gupta;G. Manes
定位是许多无线传感器网络应用的基本服务。虽然几个本地化方案依赖于锚节点和范围测量，以实现细粒度的定位，我们提出了一个范围免费，锚免费的解决方案，只使用连接信息。该方法适用于具有严格成本约束的部署，基于自组织映射（SOM）的神经网络范式。我们提出了一个轻量级的基于SOM的算法来计算虚拟坐标，是有效的位置辅助布线。该算法还可以利用几个锚节点的位置信息（如果可用的话）来计算绝对位置。广泛的模拟结果表明，流行的多维缩放（MDS）计划的改进，特别是对于具有低连接性的网络，这是本质上难以本地化，并在存在不规则的无线电模式或各向异性部署。我们分析表明，该方案具有较低的计算和通信开销，因此，使其适用于资源受限的网络。
Localization is an essential service for many wireless sensor network applications. While several localization schemes rely on anchor nodes and range measurements to achieve fine-grained positioning, we propose a range-free, anchor- free solution that works using connectivity information only. The approach, suitable for deployments with strict cost constraints, is based on the neural network paradigm of self-organizing maps (SOM). We present a lightweight SOM- based algorithm to compute virtual coordinates that are effective for location-aided routing. This algorithm can also exploit the location information, if available, of few anchor nodes to compute absolute positions. Results of extensive simulations show improvements over the popular multi-dimensional scaling (MDS) scheme, especially for networks with low connectivity, which are intrinsically harder to localize, and in presence of irregular radio pattern or anisotropic deployment. We analytically demonstrate that the proposed scheme has low computation and communication overheads; hence, making it suitable for resource-constrained networks.