Distance transform based skeleton extraction in wireless sensor networks
线传感器网络中基于距离变换的骨架提取*

In wireless sensor networks, skeleton information has been successfully used to improve routing performance; and also can be used in localization, navigation and segmentation, etc. Existing solutions often assume that all boundary nodes have been correctly recognized, in most cases, especially for networks with low node density, the boundary nodes are hardly fully identified. This paper proposed a distributed skeleton extraction algorithm of low complexity based on distance transform. The proposed algorithm did not require that all boundary nodes were correctly identified. Experiment results show that the proposed algorithm can achieve a good approximation of skeleton even under incomplete or inaccurate boundaries, and also is robust to the boundary incompleteness.