Adaptive Clustering Routing Optimization Method for Digital Mine Based on Wireless Sensor Networks

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Authors

  • Yongchun He
     Mathematics and Statistics, Yulin University, Yulin 719000, Shaanxi ,CN
  • Feng Zhang
     School of Information Engineering, Yulin University, 719000, Yulin ,CN
  • XiaLong Li
     Mathematics and Statistics, Yulin University, Yulin 719000, Shaanxi ,CN
  • Yong-Heng Zhang
     School of Information Engineering, Yulin University, 719000, Yulin ,CN

Keywords:

Digital Mine, Wireless Sensor Network, Clustering Routing Algorithm, DV-Hop Algorithm, IoT-WSNs Network.

Abstract

For digital mine applications, it has the characteristics of diverse terrain, complex weather conditions, large monitoring area, large number of sensor nodes, multi-source information for each node, and long monitoring period.With the goal of good environmental adaptability, low power consumption, low cost and standardization, the key technology of wireless sensor network for digital mine is proposed, including network structure, networking mode, node location method, data fusion method, fast self-sufficiency and energy saving strategy. For the application of digital mine, the improved DV-Hop algorithm is proposed to locate the nodes, and then by analyzing the IoT-WSNs network model and the node energy consumption model, a new clustering routing algorithm is proposed. The experimental results show that the wireless sensor network technology designed in this paper satisfies the application requirement of digital mine well. Both hardware and software are convenient for system integration, and it is suitable for standardization and large-scale popularization. The proposed algorithm is effective and reliable.

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Published

2022-10-23

How to Cite

He, Y., Zhang, F., Li, X., & Zhang, Y.-H. (2022). Adaptive Clustering Routing Optimization Method for Digital Mine Based on Wireless Sensor Networks. Journal of Mines, Metals and Fuels, 66(9), 728–732. Retrieved from http://www.informaticsjournals.com/index.php/jmmf/article/view/31791

Issue

Volume 66, Issue 9, September 2018

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

 

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