Optimal Drone Nodes Deployment to Maximize Coverage and Energy in WSNs Using Genetic Algorithms


  • Hayder Ayad Khudhair Ministry of Education, General Directorate for Education in Al-Najaf Al-Ashraf, Iraq.




Genetic Algorithms, Drone Networks, Optimization, Coverage, Lifetime


Increasing coverage and reducing the energy consumed in wireless sensor networks is an interesting field for researchers since the discovery of wireless sensor networks and it is an open problem. Activating the lowest connectivity range for each node individually depending on its remaining power and the place it covers, while maximizing coverage by placing it in the optimal place will reduce the energy consumed and increase the lifetime of wireless sensor networks. In this paper, we find an approach to increase coverage by optimizing correlation and residual energy using genetic algorithms by placing each node in the optimal position to maximize coverage, assuming that each node has a different energy from the other nodes. We will use drones to carry and move sensors to optimal position. The aim of the proposed work is to cover the largest area of a given region by using the least range of connection and increasing the Lifetime. We ran a succession of simulations and found the proposed model better than the strategies we found in literature.


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How to Cite

Ayad Khudhair, H. (2024). Optimal Drone Nodes Deployment to Maximize Coverage and Energy in WSNs Using Genetic Algorithms. Journal of Al-Qadisiyah for Computer Science and Mathematics, 16(1), COMP. 50–61. https://doi.org/10.29304/jqcsm.2024.16.11434



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