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Two-Tier PSO Based Data Routing Employing Bayesian Compressive Sensing in Underwater Sensor Networks.

Xuechen Chen1, Wenjun Xiong2, Sheng Chu2

  • 1School of Computer Science and Engineering, Central South University, Changsha 410083, China.

Sensors (Basel, Switzerland)
|October 24, 2020
PubMed
Summary

This study introduces a two-tier particle swarm optimization (PSO) algorithm for underwater wireless sensor networks, improving energy efficiency and data recovery for marine exploration.

Keywords:
Bayesian Crame´r-Rao BoundBayesian compressive sensingparticle swarm optimizationthree dimensional underwater wireless sensor network

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Area of Science:

  • Marine technology
  • Network engineering
  • Signal processing

Background:

  • Underwater acoustic sensor networks are crucial for marine data collection.
  • Optimizing sensor selection and data routing is essential for network longevity and efficiency.
  • Existing methods often struggle to balance energy consumption, network balance, and data recovery quality.

Purpose of the Study:

  • To develop an integrated approach for sensor selection and data routing in 3D underwater wireless sensor networks.
  • To enhance network lifetime and data reconstruction accuracy using Bayesian compressive sensing and PSO.
  • To analyze and incorporate the Bayesian Cramér-Rao Bound (BCRB) for improved performance monitoring.

Main Methods:

  • A two-tier Particle Swarm Optimization (PSO) approach was developed.
  • The first tier uses PSO for energy-efficient and uniform cluster head selection.
  • The second tier employs PSO for optimized one-hop and multi-hop routing, considering energy, balance, and data recovery quality.

Main Results:

  • The proposed algorithm significantly extends network lifetime by postponing the first dead node.
  • It achieves lower reconstruction errors compared to existing distributed multi-hop compressive sensing methods.
  • The integration of BCRB in the fitness function effectively monitors mean square error.

Conclusions:

  • The developed two-tier PSO algorithm offers a superior solution for 3D underwater wireless sensor networks.
  • It effectively balances energy efficiency, network stability, and data reconstruction quality.
  • This approach provides a robust framework for enhanced marine data exploration and monitoring.