TY - GEN
T1 - Efficient Multi-UAV-Aided Communication Service Deployment in Disaster-Resilient Wireless Networks
AU - Chou, Shih Fan
AU - Yu, Chen Yu
AU - Sou, Sok Ian
N1 - Funding Information:
ACKNOWLEDGEMENT The work of S.-F. Chou was supported in part by the National Science and Technology Council, Taiwan, under Grant MOST 110-2222-E-011-019-MY2. This work of S.-I. Sou was partly supported by the Ministry of Science and Technology 108-2628-E-006-006-MY3 and MOST 111-2221-E-006-123.
Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In times of disaster, a flexible and responsive emergency communication network is essential for saving lives and properties, especially after incidents such as hurricanes and floods when terrestrial base stations are not operational. Under such conditions, using Unmanned Aerial Vehicles (UAVs) as aerial base stations is a promising solution due to their agility, mobility, and flexibility. In this work, we deploy multiple UAVs in 3D space with the goal of maximizing total user service time while satisfying users' Quality-of-Service (QoS) requirements. Our proposed method divides the target area into several regions based on the Voronoi Diagram to effectively serve dynamic user distribution. By moving circles in each region, we can discover the optimal placement of service areas. Then, we deploy UAVs to service areas with maximum total service time. Our simulation results demonstrate the effectiveness of our approach in the total service time while fulfilling the QoS requirements of all served users.
AB - In times of disaster, a flexible and responsive emergency communication network is essential for saving lives and properties, especially after incidents such as hurricanes and floods when terrestrial base stations are not operational. Under such conditions, using Unmanned Aerial Vehicles (UAVs) as aerial base stations is a promising solution due to their agility, mobility, and flexibility. In this work, we deploy multiple UAVs in 3D space with the goal of maximizing total user service time while satisfying users' Quality-of-Service (QoS) requirements. Our proposed method divides the target area into several regions based on the Voronoi Diagram to effectively serve dynamic user distribution. By moving circles in each region, we can discover the optimal placement of service areas. Then, we deploy UAVs to service areas with maximum total service time. Our simulation results demonstrate the effectiveness of our approach in the total service time while fulfilling the QoS requirements of all served users.
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U2 - 10.1109/VNC57357.2023.10136334
DO - 10.1109/VNC57357.2023.10136334
M3 - Conference contribution
AN - SCOPUS:85163187344
T3 - IEEE Vehicular Networking Conference, VNC
SP - 1
EP - 8
BT - 2023 IEEE Vehicular Networking Conference, VNC 2023
A2 - Coleri, Sinem
A2 - Altintas, Onur
A2 - Kargl, Frank
A2 - Higuchi, Takamasa
A2 - Segata, Michele
A2 - Klingler, Florian
PB - IEEE Computer Society
T2 - 14th IEEE Vehicular Networking Conference, VNC 2023
Y2 - 26 April 2023 through 28 April 2023
ER -