Paper
20 September 2024 Lora gateway coverage optimization based on improved firefly algorithm
Longxiang Li, Youfu Jiang, Kaihao Hu, Junhu Jia
Author Affiliations +
Proceedings Volume 13269, Fourth International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2024); 132690W (2024) https://doi.org/10.1117/12.3045481
Event: Fourth International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2024), 2024, Kuala Lumpur, Malaysia
Abstract
In order to improve the coverage of Lora gateway communication, taking the coverage of Lora gateway as the maximum target, an improved firefly algorithm based gateway coverage optimization method (IFA) was proposed. Firstly, the Lora gateway communication coverage model is constructed according to the coverage area and the number of the gateway. Secondly, based on the firefly algorithm, particle swarm optimization algorithm is applied to improve the location of the gateway node during its movement, which can effectively improve the coverage uniformity of the gateway, and the coverage of the gateway area can be achieved by simulating the number of Lora gateways through the number of fireflies. Finally, the coverage area of the gateway can be maximized by the improved firefly algorithm. The simulation results show that compared with the basic firefly algorithm and genetic algorithm, the proposed algorithm can consume less resources to achieve better optimization effect, and the coverage rate is improved by 22.54% compared with the previous algorithm, and the coverage rate of gateway nodes is improved better.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Longxiang Li, Youfu Jiang, Kaihao Hu, and Junhu Jia "Lora gateway coverage optimization based on improved firefly algorithm", Proc. SPIE 13269, Fourth International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2024), 132690W (20 September 2024); https://doi.org/10.1117/12.3045481
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KEYWORDS
Particle swarm optimization

Mathematical optimization

Particles

Computer simulations

Detection and tracking algorithms

Genetical swarm optimization

Sensor networks

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