Fast Trajectory Planning for UAV-Enabled Maritime IoT Systems: A Fermat-Point Based Approach

被引：21
作者：
Lyu, Ling [1 ,2 ]
Chu, Zhenhang [1 ]
Lin, Bin [1 ,3 ]
Dai, Yanpeng [1 ]
Cheng, Nan [4 ]
机构：
[1] Dalian Maritime Univ, Sch Informat Sci & Technol, Dalian 116026, Peoples R China
[2] Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Shaanxi, Peoples R China
[3] Peng Cheng Lab, Network Commun Res Ctr, Shenzhen 518052, Peoples R China
[4] Xidian Univ, Sch Telecommun Engn, Xian 710071, Shaanxi, Peoples R China
来源：
IEEE WIRELESS COMMUNICATIONS LETTERS | 2022年 / 11卷 / 02期
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
Trajectory planning; Unmanned aerial vehicles; Monitoring; Trajectory; Sea surface; Propellers; Internet of Things; Maritime IoT systems; trajectory planning; UAV-enabled data collection; fermat-point; BIG DATA;
D O I：
10.1109/LWC.2021.3127205
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This letter proposes a fast Unmanned Aerial Vehicle (UAV) trajectory planning algorithm based on the Fermat-point theory in maritime Internet of Things systems. Specifically, we first construct Delaunay triangles based on the deployment of unmanned surface vehicles. Then, the Fermat point of each Delaunay triangle is calculated and as a hovering point of UAVs to improve the channel condition. Finally, the trajectory planning problem can be transformed into a vehicle routing problem with pickup, which is solved by the proposed algorithm based on C-W saving method. Simulation results show the proposed algorithm can efficiently increase collected data volume of UAVs.
引用
收藏
页码：328 / 332
页数：5
相关论文
共 12 条
  • [1] Gorobetz M., 2015, P 56 INT SCI C POW E, P1
  • [2] Maritime Coverage Enhancement Using UAVs Coordinated With Hybrid Satellite-Terrestrial Networks
    Li, Xiangling
    Feng, Wei
    Chen, Yunfei
    Wang, Cheng-Xiang
    Ge, Ning
    [J]. IEEE TRANSACTIONS ON COMMUNICATIONS, 2020, 68 (04) : 2355 - 2369
  • [3] MARINE WIRELESS BIG DATA: EFFICIENT TRANSMISSION, RELATED APPLICATIONS, AND CHALLENGES
    Li, Yuzhou
    Zhang, Yu
    Li, Wei
    Jiang, Tao
    [J]. IEEE WIRELESS COMMUNICATIONS, 2018, 25 (01) : 19 - 25
  • [4] A low-cost physical location discovery scheme for large-scale Internet of Things in smart city through joint use of vehicles and UAVs
    Teng, Haojun
    Dong, Mianxiong
    Liu, Yuxin
    Tian, Wang
    Liu, Xuxun
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2021, 118 : 310 - 326
  • [5] Unmanned Aerial Vehicle-Aided Communications: Joint Transmit Power and Trajectory Optimization
    Wang, Haichao
    Ren, Guochun
    Chen, Jin
    Ding, Guoru
    Yang, Yijun
    [J]. IEEE WIRELESS COMMUNICATIONS LETTERS, 2018, 7 (04) : 522 - 525
  • [6] Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges
    Wei, Te
    Feng, Wei
    Chen, Yunfei
    Wang, Cheng-Xiang
    Ge, Ning
    Lu, Jianhua
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (11) : 8910 - 8934
  • [7] Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks
    Wu, Qingqing
    Zeng, Yong
    Zhang, Rui
    [J]. IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2018, 17 (03) : 2109 - 2121
  • [8] Xing W, 2016, PROCEEDINGS OF 2016 2ND INTERNATIONAL CONFERENCE ON CONTROL SCIENCE AND SYSTEMS ENGINEERING (ICCSSE), P1, DOI 10.1109/CCSSE.2016.7784340
  • [9] Big Data on the Fly: UAV-Mounted Mobile Edge Computing for Disaster Management
    Xu, Jianwen
    Ota, Kaoru
    Dong, Mianxiong
    [J]. IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2020, 7 (04): : 2620 - 2630
  • [10] Deploying SDN Control in Internet of UAVs: Q-Learning-Based Edge Scheduling
    Zhang, Chaofeng
    Dong, Mianxiong
    Ota, Kaoru
    [J]. IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2021, 18 (01): : 526 - 537
12