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Maximum Target Coverage Problem in Mobile Wireless Sensor Networks.

Dieyan Liang1, Hong Shen1, Lin Chen1

  • 1School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou 510006, China.

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Summary
This summary is machine-generated.

This study addresses wireless sensor network coverage optimization for mobile sensors with limited movement. It introduces approximation algorithms to maximize target coverage efficiently.

Keywords:
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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Optimization

Background:

  • Wireless sensor networks (WSNs) are crucial for monitoring applications.
  • Optimizing sensor deployment and movement is essential for effective coverage.
  • Limited sensor mobility presents unique challenges in WSN coverage problems.

Purpose of the Study:

  • To formulate and analyze a generic coverage optimization problem for WSNs with mobile sensors.
  • To develop efficient algorithms for maximizing target coverage under movement constraints.
  • To address the NP-hard nature of the problem through heuristic and approximation methods.

Main Methods:

  • Formulation of a generic coverage optimization problem.
  • Proof of NP-hardness for the formulated problem.
  • Development of four algorithms: one randomized approximation and three deterministic approximation algorithms.
  • Application of derandomization techniques and coloring techniques for approximation algorithms.

Main Results:

  • The coverage optimization problem in WSNs with limited sensor mobility is proven to be NP-hard.
  • A randomized (1-1/e)-approximation algorithm was developed.
  • A deterministic (1-1/e)-approximation algorithm using derandomization was devised.
  • A deterministic approximation algorithm with a nearly Δ-1 approximation ratio was designed using coloring techniques.
  • Experimental validation demonstrated the effectiveness of the proposed algorithms.

Conclusions:

  • The proposed algorithms provide effective solutions for the NP-hard coverage optimization problem in WSNs.
  • The algorithms offer different trade-offs between performance and complexity.
  • The study contributes practical methods for enhancing WSN coverage with mobile sensors.