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Photonic Network Communications

, Volume 37, Issue 2, pp 224–232 | Cite as

Nodes deployment optimization algorithm based on improved evidence theory of underwater wireless sensor networks

  • Xiaoli SongEmail author
  • Yunzhan Gong
  • Dahai Jin
  • Qiangyi Li
Original Paper

Abstract

Underwater wireless sensor networks (UWSNs) applications for ocean monitoring, deep sea surveillance, and locating natural resources are gaining more and more popularity. To monitor the underwater environment or any object within a certain area of interest, these applications are required to deploy underwater node sensors connected for obtaining useful data. For thriving UWSNs, it is essential that an efficient and secure node deployment mechanism is in place. This paper presents a novel node deployment scheme, which is based on evidence theory approach and caters for 3D USWNs. This scheme implements sonar probability perception and an enhanced data fusion model to improve prior probability deployment algorithm of D–S evidence theory. The viability of our algorithm is verified by performing multiple simulation experiments. The simulation results reveal that our algorithm deploys fewer nodes with enhanced network judgment criteria and expanded detection capabilities for a relatively large coverage area compared to other schemes. In addition, the generated nodes are also less resource intensive, i.e., low-power sensor nodes.

Keywords

Evidence theory Nodes deployment algorithm Underwater wireless sensor networks Data fusion Coverage 

Notes

Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (NSFC) under Grant No. U1736110. The authors also gratefully acknowledge the helpful comments and suggestions of the editors and reviewers, which have improved the presentation.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Xiaoli Song
    • 1
    • 2
    Email author
  • Yunzhan Gong
    • 1
  • Dahai Jin
    • 1
  • Qiangyi Li
    • 2
  1. 1.State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijingChina
  2. 2.Henan University of Science and TechnologyLuoyangChina

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