An Optimal Method to Design Wireless Sensor Network Structures

Authors

  • Yang Ling Zhongkai University of Agriculture and Engineering
  • Cai Xucan Zhongkai University of Agriculture and Engineering
  • Wu Chunlin Zhongkai University of Agriculture and Engineering

DOI:

https://doi.org/10.3991/ijoe.v14i01.8062

Keywords:

wireless sensor networks, dormancy mechanism, reconstruction, wake up, node mobility

Abstract


In order to optimize the structure of wireless sensor network, an improved wireless sensor network sleep mechanism is proposed. First, some nodes in the area with too high redundancy are dormant by density control, so that the active nodes are even more distributed. Then, the active node is subjected to circular coverage redundancy decision. Different circumferential coverage decision methods are used for network boundary nodes and non-boundary nodes. As a result, the boundary nodes and non-boundary nodes are well dormant, and the network redundancy is reduced. The simulation results show that the improved dormancy mechanism makes the number of active nodes in the network smaller and more evenly, and the network lifetime is extended on the basis of maintaining the original coverage of the network. Therefore, the proposed method can achieve optimal coverage in wireless sensor networks. The network prolongs network lifetime while ensuring reliable monitoring performance.

Author Biographies

Yang Ling, Zhongkai University of Agriculture and Engineering

School of Information Science and Technology

Cai Xucan, Zhongkai University of Agriculture and Engineering

School of Information Science and Technology

Wu Chunlin, Zhongkai University of Agriculture and Engineering

School of Information Science and Technology

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Published

2018-01-25

How to Cite

Ling, Y., Xucan, C., & Chunlin, W. (2018). An Optimal Method to Design Wireless Sensor Network Structures. International Journal of Online and Biomedical Engineering (iJOE), 14(01), pp. 40–51. https://doi.org/10.3991/ijoe.v14i01.8062

Issue

Vol. 14 No. 01 (2018)

Section

Papers

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