UAV Placement Optimization for Internet of Medical Things

Tang，Chaogang1; Zhu，Chunsheng2,3; Wei，Xianglin4; Rodrigues，Joel J.P.C.5,6; Guizani，Mohsen7; Jia，Weijia8

10.1109/IWCMC48107.2020.9148581

2020-06-01

2020 International Wireless Communications and Mobile Computing, IWCMC 2020

752-757

Internet of Medical Things (IoMT), intended for real-time health monitoring, are generating quantity of health data such as electrocardiogram, oxygen saturation, and blood pressure every second. The captured data should be processed and analyzed in a delay sensitive way which is vital to the survival rate for cardiovascular and cerebrovascular diseases. In this regard, Unmanned Aerial Vehicles (UAVs) have already demonstrated the enormous potentials. To begin with, due to better line-of-sight, wider communication and more flexible on-demand deployment, UAVs can realize seamless wireless connection to IoMT. Furthermore, UAVs can act as fog nodes to provision services for IoMTs such as task performing and data analysis. We in this paper focus on a sub-problem, i.e., the placement of UAVs over the serving area when they function as fog nodes. In the airborne fog computing, the placement of UAVs has an important influence on energy consumption and exploration area, let alone the communication coverage of the personal health devices on the ground. Therefore, we in this paper propose a particle swarm optimization (PSO) based algorithm to optimize the UAV placement over the serving area for the IoMT devices. We have conducted extensive simulations to evaluate it. The results show that our approach can significantly reduce the number of UAVs needed to deploy while considering the communication coverage and other factors.

airborne fog computing health IoMT placement UAV

其他

英语

EI

20203409090356

Energy utilization ; Fog ; Fog computing ; Blood pressure ; Particle swarm optimization (PSO) ; Unmanned aerial vehicles (UAV) ; Antennas ; Delay-sensitive applications

Atmospheric Properties:443.1 ; Medicine and Pharmacology:461.6 ; Biology:461.9 ; Energy Utilization:525.3 ; Aircraft, General:652.1 ; Digital Computers and Systems:722.4 ; Computer Software, Data Handling and Applications:723 ; Control System Applications:731.2 ; Optimization Techniques:921.5

2-s2.0-85089660740

Scopus

1.School of Computer Science and Technology,China University of Mining and Technology,Xuzhou,China
2.SUSTech Institute of Future Networks,Southern University of Science and Technology,Shenzhen,China
3.Pcl Research Center of Networks and Communications,Peng Cheng Laboratory,Shenzhen,China
4.Nanjing Telecommunication Technology Research Institute,Nanjing,China
5.Federal University of Piaui,Teresina - Pi,Brazil
6.Instituto de Telecomunicacoes,Portugal
7.Department of Computer Science and Engineering,Qatar University,Qatar
8.Faculty of Science and Technology,University of Macau,Taipa,Macao

Tang，Chaogang,Zhu，Chunsheng,Wei，Xianglin,et al. UAV Placement Optimization for Internet of Medical Things[C],2020:752-757.