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A Novel Skeleton Extraction Algorithm in Sensor Networks

  • DongHui Zhu
  • Yubao Wang
  • Jing Xing
  • Wenping Liu
  • Hongbo Jiang
  • Gang Wu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 295)

Abstract

This paper analyzes the problem of location-free skeleton extraction in sensor networks . Different from most of the previous solutions, the proposed algorithm has no dependency on boundary information. Our work is based on the proposed index of a node, named centrality, which can reflect the centeredness of the node. We first identify the node having the maximal centrality as the root skeleton node, based on whether a skeleton arc is obtained. Secondly, each node then computes its hop count distance to the skeleton arc, and the network is decomposed into a set of level sets. The node with the maximal centrality is identified as a skeleton node. Thirdly, these skeleton nodes are connected properly to form a coarse skeleton possibly with spurious branches. Finally, a pruning operation is conducted on the coarse skeleton, and the final skeleton is generated. Extensive simulations show the efficiency of the proposed algorithm.

Keywords

Sensor networks Skeleton Location-free Boundary-free Centrality 

Notes

Acknowledgments

This work was supported in part by the National Natural Science Foundation of China under Grant 61202460.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • DongHui Zhu
    • 1
  • Yubao Wang
    • 1
  • Jing Xing
    • 1
  • Wenping Liu
    • 1
    • 2
  • Hongbo Jiang
    • 2
  • Gang Wu
    • 2
  1. 1.Hubei University of EconomicsWuhanChina
  2. 2.Huazhong University of Science and TechnologyWuhanChina

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