A distributed delaunay triangulation algorithm based on centroidal voronoi tessellation for wireless sensor networks

Hongyu Zhou, Miao Jin, Hongyi Wu
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引用次数: 16

Abstract

A wireless sensor network can be represented by a graph. While the network graph is extremely useful, it often exhibits undesired irregularity. Therefore, special treatment of the graph is required by a variety of network algorithms and protocols. In particular, many geometry-oriented algorithms depend on a type of subgraph called Delaunay triangulation. However, when location information is unavailable, it is nontrivial to achieve Delaunay triangulation by using connectivity information only. The only connectivity-based algorithm available for Delaunay triangulation is built upon the property that the dual graph for a Voronoi diagram is a Delaunay triangulation. This approach, however, often fails in practical wireless sensor networks because the boundaries of Voronoi cells can be arbitrarily short in discrete sensor network settings. In a sensor network with connectivity information only, it is fundamentally unattainable to correctly judge neighboring cells when a Voronoi cell boundary is less than one hop. Consequently, the Voronoi diagram-based Delaunay triangulation fails. The proposed algorithm employs a distributed approach to perform centroidal Voronoi tessellation, and constructs its dual graph to yield Delaunay triangulation. It exhibits several distinctive properties. First, it eliminates the problem due to short cell boundaries and thus effectively avoids crossing edges. Second, the proposed algorithm is proven to converge and succeed in constructing a Delaunay triangulation, if the CVT cell size is greater than a constant threshold. Third, the established Delaunay triangulation consists of close-to-equilateral triangles, benefiting a range of applications such as geometric routing, localization, coverage, segmentation, and data storage and processing. Extensive simulations are carried out under various 2D network models to evaluate the effectiveness and efficiency of the proposed CVT-based triangulation algorithm.
一种基于质心voronoi镶嵌的无线传感器网络分布式延迟三角剖分算法
无线传感器网络可以用图形表示。虽然网络图非常有用,但它经常表现出不希望看到的不规则性。因此,各种网络算法和协议都需要对图进行特殊处理。特别是,许多面向几何的算法依赖于一种称为Delaunay三角剖分的子图。然而,当位置信息不可用时,仅使用连接信息来实现Delaunay三角测量是非常重要的。唯一可用于Delaunay三角剖分的基于连通性的算法是建立在Voronoi图的对偶图是Delaunay三角剖分的属性之上的。然而,这种方法在实际的无线传感器网络中经常失败,因为在离散的传感器网络设置中,Voronoi细胞的边界可以任意短。在只有连通性信息的传感器网络中,当Voronoi细胞边界小于一跳时,从根本上无法正确判断相邻细胞。因此,基于Voronoi图的Delaunay三角剖分失败。该算法采用分布式方法进行质心Voronoi镶嵌,并构造其对偶图,得到Delaunay三角剖分。它有几个独特的特性。首先,它消除了单元边界短的问题,从而有效地避免了交叉边缘。其次,当CVT单元的大小大于一个常数阈值时,证明了该算法的收敛性,并成功构建了Delaunay三角剖分。第三,建立的Delaunay三角剖分由接近等边的三角形组成,有利于几何路由、定位、覆盖、分割、数据存储和处理等一系列应用。在各种二维网络模型下进行了大量的仿真,以评估所提出的基于cvt的三角剖分算法的有效性和效率。
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