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Target Coverage in Wireless Sensor Networks with Probabilistic Sensors.

Anxing Shan1, Xianghua Xu2, Zongmao Cheng3

  • 1School of Computer Science, Hangzhou Dianzi University, Hangzhou 310018, China. 141050025@hdu.edu.cn.

Sensors (Basel, Switzerland)
|September 14, 2016
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Summary
This summary is machine-generated.

This study addresses wireless sensor network (WSN) coverage using a probabilistic model, moving beyond simple 0/1 approximations. It introduces an algorithm to find the minimum sensors for reliable target detection, proving its effectiveness.

Keywords:
probabilistic sensortarget coveragewireless sensor networks

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Traditional wireless sensor network (WSN) coverage models (0/1) offer limited accuracy for real-world sensing scenarios.
  • The need for more sophisticated models that account for probabilistic sensing is critical for WSN deployment.
  • Randomly deployed WSNs present unique challenges for achieving effective sensing coverage.

Purpose of the Study:

  • To investigate the target coverage problem in WSNs using a probabilistic sensing model.
  • To formulate and address the minimum epsilon-detection coverage problem.
  • To develop and evaluate an efficient approximation algorithm for probabilistic sensor coverage.

Main Methods:

  • Analysis of joint detection probability for multiple sensors in WSNs.
  • Formulation of the minimum epsilon-detection coverage problem based on theoretical probability analysis.
  • Development of the Probabilistic Sensor Coverage Algorithm (PSCA) with provable approximation ratios.

Main Results:

  • The minimum epsilon-detection coverage problem is proven to be NP-hard.
  • The proposed Probabilistic Sensor Coverage Algorithm (PSCA) demonstrates provable approximation ratios.
  • Extensive simulations confirm the effectiveness of PSCA in achieving probabilistic sensing coverage.

Conclusions:

  • The probabilistic sensing model provides a more realistic approach to WSN coverage than the 0/1 model.
  • PSCA offers an effective solution for the NP-hard minimum epsilon-detection coverage problem.
  • The algorithm is validated through theoretical analysis and simulations, highlighting its practical utility.