基于面翻转三维传感器网络边界节点识别算法

Boundary node identification algorithm for three-dimensional sensor networks based on flipping plane

针对三维环境下的传感器网络边界节点识别问题,提出了一种基于面翻转的传感器网络边界节点分布式识别方法。算法在已知三个相邻边界节点的基础上,以三个相邻边界节点构成的三角形的各边为轴,以有限面积的面向网络外侧翻转,扫描到的第一个点为新的边界节点,该节点与翻转轴上的两个节点构建成新三角形,迭代上述过程,最终识别出边界节点,获取边界包络。实验结果表明,与Alpha-shape3D算法相比,所提算法能大大减少冗余边界节点。

In view of the sensor network boundary identification in 3D environment, this paper presented a distributed algorithm for boundary node identification based on flipping finite plane. Based on three known adjacent nodes, the finite plane took each edge of triangle as axis to flip, the first node scanned is the new boundary node, this node and two nodes on the axis construct a new triangle. Above process was carried out iteratively, eventually the boundary contour was got and the boundary nodes were identified. The experimental result shows that, compared with Alpha-shape3D algorithm, the proposed algorithm can greatly reduce the redundant boundary nodes.