Holes Detection in Anisotropic Sensornets: Topological Methods
Holes Detection in Anisotropic Sensornets: Topological Methods
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DOI：
10.1155/2012/135054
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发表时间：
2012-10
影响因子：
2.3
通讯作者：
Wei Wei-Wei;Xiaolin Yang;Peiyi Shen;Bin Zhou
中科院分区：
文献类型：
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作者：
Wei Wei-Wei;Xiaolin Yang;Peiyi Shen;Bin Zhou
无线传感器网络（WSN）与部署传感器的实际环境紧密相关。传感器定位是利用传感器网络的主要位置相关应用的关键部分。网络的全局拓扑对于传感器网络应用和网络功能的实现都很重要。本文研究了拓扑发现，重点是传感器网络中的边界识别。大量传感器节点应该分散在一个几何区域中，附近的节点直接相互通信。因此，本文旨在仅通过连接信息来检测传感器网络拓扑结构中的漏洞。现有的边缘确定方法以高成本为假设。如果没有大量统一部署的种子节点的帮助，这些方案在可能存在漏洞的各向异性无线传感器网络中会失败。针对这个问题，我们提出了一种基于Poincare-Perelman定理的PPA解决方案，来判断WSN监控区域是否存在漏洞。我们的解决方案可以正确检测拓扑表面上的孔并将它们连接成有意义的边界循环。该判断方法也被严格证明适用于连续几何域以及离散域。大量的模拟表明，该算法甚至可以使低密度的网络产生良好的结果。
Wireless sensor networks (WSNs) are tightly linked with the practical environment in which the sensors are deployed. Sensor positioning is a pivotal part of main location-dependent applications that utilize sensornets. The global topology of the network is important to both sensor network applications and the implementation of networking functionalities. This paper studies the topology discovery with an emphasis on boundary recognition in a sensor network. A large mass of sensor nodes are supposed to scatter in a geometric region, with nearby nodes communicating with each other directly. This paper is thus designed to detect the holes in the topological architecture of sensornets only by connectivity information. Existent edges determination methods hold the high costs as assumptions. Without the help of a large amount of uniformly deployed seed nodes, those schemes fail in anisotropic WSNs with possible holes. To address this issue, we propose a solution, named PPA based on Poincare-Perelman Theorem, to judge whether there are holes in WSNs-monitored areas. Our solution can properly detect holes on the topological surfaces and connect them into meaningful boundary cycles. The judging method has also been rigorously proved to be appropriate for continuous geometric domains as well as discrete domains. Extensive simulations have been shown that the algorithm even enables networks with low density to produce good results.