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An Enhanced Particle Swarm Optimization-Based Node Deployment and Coverage in Sensor Networks.

Kondisetty Venkata Naga Aruna Bhargavi1, Gottumukkala Partha Saradhi Varma2, Indukuri Hemalatha3

  • 1Computer Science Engineering, Koneru Lakshmaiah Education Foundation, Hyderabad 500075, Telengana, India.

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Summary

This study optimizes wireless sensor network (WSN) coverage by using an enhanced particle swarm optimization (EPSO) algorithm to strategically position sensor nodes, significantly improving detection probability and reducing deployment redundancy.

Keywords:
Delaunay triangulationcoverage problemparticle swarm optimizationsensor node deploymentwireless sensor network

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Area of Science:

  • Wireless communication networks
  • Sensor network optimization
  • Coverage enhancement algorithms

Background:

  • Wireless Sensor Networks (WSNs) are crucial for monitoring regions of interest (ROI).
  • Random sensor node deployment and battery depletion lead to poor coverage and coverage holes.
  • Optimal sensor node positioning is essential for effective WSN coverage.

Purpose of the Study:

  • To define optimal sensor node locations before deployment in a WSN.
  • To increase the coverage area using an enhanced particle swarm optimization (EPSO) algorithm.
  • To evaluate performance across different frequency bands (3.6 GHz, 26 GHz, 38 GHz).

Main Methods:

  • Proposed an enhanced particle swarm optimization (EPSO) algorithm for node placement.
  • Utilized a probabilistic coverage model based on Euclidean distances to identify coverage gaps.
  • Combined EPSO with Delaunay triangulation (DT) to optimize node positions and fill coverage holes.

Main Results:

  • The EPSO algorithm successfully avoided node proximity and ensured target coverage.
  • Achieved converged results with an average of 78-82 iterations across frequency bands.
  • Demonstrated significantly improved coverage with a 4 m communication radius compared to existing methods (6-120 m).

Conclusions:

  • The proposed EPSO-DT approach effectively enhances WSN coverage and optimizes node deployment.
  • The method guarantees higher coverage probability and addresses issues of random deployment.
  • Optimized sensor node positioning is critical for next-generation wireless network applications.