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Title: Gathering data in wireless sensor networks by drone.
Authors: Rezende, Josiane da Costa Vieira
metadata.dc.contributor.advisor: Souza, Marcone Jamilson Freitas
Silva, Rone Ilídio da
Keywords: Redes locais sem fio
Computação móvel
Issue Date: 2020
metadata.dc.contributor.referee: Souza, Marcone Jamilson Freitas
Teixeira, Fernando Augusto
Coelho, Igor Machado
Ochi, Luiz Satoru
Penna, Puca Huachi Vaz
Coelho, Vitor Nazário
Silva, Rone Ilidio da
Citation: REZENDE, Josiane da Costa Vieira. Gathering data in wireless sensor networks by drone. 2020. 62 f. Tese (Doutorado em Ciência da Computação) - Instituto de Ciências Exatas e Biológicas, Universidade Federal de Ouro Preto, Ouro Preto, 2020.
Abstract: The benefits of using mobile sinks or data mules for data collection in Wireless Sensor Network (WSN) have been studied in several studies. However, most of them consider only the WSN limitations and sensor nodes having no more than one data packet to transmit. This paper considers each sensor node having a relatively larger volume of data stored in its memory. That is, they have several data packets to send to sink. We also consider a drone with hovering capability, such as a quad-copter, as a mobile sink to gather this data. Hence, the mobile collector eventually has to hover to guarantee that all data will be received. Drones, however, have a limited power supply that restricts their flying time. Hence, the drone’s energy cost must also be considered to increase the amount of collected data from the WSN. This work investigates the problem of determining the best drone tour for data gathering in a WSN. We focus on minimizing the overall drone flight time needed to collect all data from the WSN. We propose an algorithm to create a subset of sensor nodes to send data to the drone during its movement and, consequently, reduce its hovering time. The proposed algorithm guarantees that the drone will stay a minimum time inside every sensor node’s radio range. The computational experiments showed that our proposal significantly outperforms the state-of-the-art methods in finding drone tours in this type of scenario.
Description: Programa de Pós-Graduação em Ciência da Computação. Departamento de Ciência da Computação, Instituto de Ciências Exatas e Biológicas, Universidade Federal de Ouro Preto.
metadata.dc.rights.license: Autorização concedida ao Repositório Institucional da UFOP pelo(a) autor(a) em 25/03/2021 com as seguintes condições: disponível sob Licença Creative Commons 4.0 que permite copiar, distribuir e transmitir o trabalho, desde que sejam citados o autor e o licenciante. Não permite o uso para fins comerciais.
Appears in Collections:PPGCC - Doutorado (Teses)

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