TY - JOUR
T1 - Dynamic positioning of UAVs to improve network coverage in VANETs
AU - Islam, Md Mahmudul
AU - Khan, Muhammad Toaha Raza
AU - Saad, Malik Muhammad
AU - Tariq, Muhammad Ashar
AU - Kim, Dongkyun
N1 - Publisher Copyright:
© 2022 Elsevier Inc.
PY - 2022/8
Y1 - 2022/8
N2 - Unmanned aerial vehicles (UAVs) are expected to become an essential component of the future wireless networks, opening up a plethora of options to improve communications between vehicles and infrastructures. In addition, Road Side Units (RSUs) are deployed in a limited number to reduce the monetary cost leads to many uncovered regions in the network. Motivated by this, we propose a collaborative network coverage enhancement scheme (CONEC) to bring the uncovered vehicles within the infrastructure's coverage. In this paper, we leverage the UAVs to facilitate seamless network coverage for ground vehicles by optimally placing the UAVs in optimal places. To this end, we utilize the Particle Swarm Optimization (PSO) algorithm to find the best UAV deployment position in the whole network while considering vehicle density, heading direction, and previous coverage information. After that, PSO is called successively to obtain the optimal number of UAVs required to provide coverage to vehicles up to predefined network coverage threshold. Furthermore, we propose additional algorithm to efficiently schedule the UAVs in each time frame to minimize the wastage of UAVs service time. The simulation results demonstrate that the proposed scheme CONEC improves the network performance of VANET in terms of packet delivery ratio (PDR), hop counts (HOPs), end-to-end delay (EED), and throughput compared to its counterpart.
AB - Unmanned aerial vehicles (UAVs) are expected to become an essential component of the future wireless networks, opening up a plethora of options to improve communications between vehicles and infrastructures. In addition, Road Side Units (RSUs) are deployed in a limited number to reduce the monetary cost leads to many uncovered regions in the network. Motivated by this, we propose a collaborative network coverage enhancement scheme (CONEC) to bring the uncovered vehicles within the infrastructure's coverage. In this paper, we leverage the UAVs to facilitate seamless network coverage for ground vehicles by optimally placing the UAVs in optimal places. To this end, we utilize the Particle Swarm Optimization (PSO) algorithm to find the best UAV deployment position in the whole network while considering vehicle density, heading direction, and previous coverage information. After that, PSO is called successively to obtain the optimal number of UAVs required to provide coverage to vehicles up to predefined network coverage threshold. Furthermore, we propose additional algorithm to efficiently schedule the UAVs in each time frame to minimize the wastage of UAVs service time. The simulation results demonstrate that the proposed scheme CONEC improves the network performance of VANET in terms of packet delivery ratio (PDR), hop counts (HOPs), end-to-end delay (EED), and throughput compared to its counterpart.
KW - Network coverage
KW - RSUs
KW - UAV placement optimization
KW - UAVs
KW - VANETs
UR - http://www.scopus.com/inward/record.url?scp=85133192822&partnerID=8YFLogxK
U2 - 10.1016/j.vehcom.2022.100498
DO - 10.1016/j.vehcom.2022.100498
M3 - Article
AN - SCOPUS:85133192822
SN - 2214-2096
VL - 36
JO - Vehicular Communications
JF - Vehicular Communications
M1 - 100498
ER -