ICMAME 2023 Conference Proceedings
Paper No: 253
Paper Title: UAV’s enhanced data collection for heterogeneous wireless sensor networks
Paper Title: UAV’s enhanced data collection for heterogeneous wireless sensor networks
AUTHORS:
Kamel BARKA Computer Science Department, LaSTIC Laboratory Batna 2 University, Batna, Algeria
Lyamine GUEZOULI Renewable Energies and New Technologies Department, LEREESI Laboratory Higher National School of Renewable Energies, Environment & Sustainable Development, Batna, Algeria
Assem REZKI Computer Science Department, LaSTIC Laboratory Batna 2 University, Batna, Algeria
ABSTRACT:
In this article, we propose a protocol called DataGA-DRF (a protocol for Data collection using a Genetic Algorithm through Dynamic Reference Points) that collects data from Heterogeneous wireless sensor networks. This protocol is based on DGA (Destination selection according to Genetic Algorithm) to control the movement of the UAV (Unmanned aerial vehicle) between dynamic reference points that virtually represent the sensor node deployment. The dynamics of these points ensure an even distribution of energy consumption among the sensors and also improve network performance. To determine the best points, DataGA-DRF uses a classification algorithm such as K-Means.
Keywords: Proportional Integral Derivative (PID), Swarm Intelligence (SI), Renewable Energy (RE), Statistical Analysis
Conference Venue: Mövenpick Hotel & Apartments Bur Dubai, Dubai-UAE
Conference Date: 29-30 April 2023
ISBN Number: 978-625-00-1526-1
DOI Number: https://doi.org/10.53375/icmame.2023.253
PDF Download
Kamel BARKA Computer Science Department, LaSTIC Laboratory Batna 2 University, Batna, Algeria
Lyamine GUEZOULI Renewable Energies and New Technologies Department, LEREESI Laboratory Higher National School of Renewable Energies, Environment & Sustainable Development, Batna, Algeria
Assem REZKI Computer Science Department, LaSTIC Laboratory Batna 2 University, Batna, Algeria
ABSTRACT:
In this article, we propose a protocol called DataGA-DRF (a protocol for Data collection using a Genetic Algorithm through Dynamic Reference Points) that collects data from Heterogeneous wireless sensor networks. This protocol is based on DGA (Destination selection according to Genetic Algorithm) to control the movement of the UAV (Unmanned aerial vehicle) between dynamic reference points that virtually represent the sensor node deployment. The dynamics of these points ensure an even distribution of energy consumption among the sensors and also improve network performance. To determine the best points, DataGA-DRF uses a classification algorithm such as K-Means.
Keywords: Proportional Integral Derivative (PID), Swarm Intelligence (SI), Renewable Energy (RE), Statistical Analysis
Conference Venue: Mövenpick Hotel & Apartments Bur Dubai, Dubai-UAE
Conference Date: 29-30 April 2023
ISBN Number: 978-625-00-1526-1
DOI Number: https://doi.org/10.53375/icmame.2023.253
PDF Download