Coverage maximization of sensor networks with connectivity constraints in obstacle-filled environment based on nature-inspired algorithms

Authors

  • Quang Anh Tran Hanoi University of Science and Technology
  • Huy Tuyen Pham Hanoi University of Science and Technology
  • Phuong Du Tran Hanoi University of Science and Technology
  • Son Tran Hanoi University of Science and Technology
  • Duc Chinh Hoang Hanoi University of Science and Technology

DOI:

https://doi.org/10.64032/mca.v29i2.288

Keywords:

Wireless Sensor Networks, Node Deployment, CC-CM problem, Metaheuristic algorithms

Abstract

The application of meta-heuristic algorithms has significant potential in various fields, including wireless sensor networks. In this paper, we utilize two algorithms, the Fruitfly optimization algorithm (FOA) and the Nutcracker optimization algorithm (NOA), to address two critical issues: optimizing coverage and ensuring connectivity in sensor networks. The main contribution of this paper is the application of these algorithms to arbitrary communication radius, independent of predefined connectivity assumptions. Simulation results demonstrate the effectiveness of the proposed methods by comparing with each other and with the two traditional algorithms Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Additionally, this paper simulates the coverage area in an environment with different types of obstacles to showcase the practical flexibility of the algorithms.

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Published

17-06-2025

How to Cite

Tran, Q. A., Pham, H. T., Tran, P. D., Tran, S., & Hoang, D. C. (2025). Coverage maximization of sensor networks with connectivity constraints in obstacle-filled environment based on nature-inspired algorithms. Journal of Measurement, Control, and Automation, 29(2), 73–79. https://doi.org/10.64032/mca.v29i2.288

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