UAV Trajectory Optimization in a Post-Disaster Area Using Dual Energy-Aware Bandits

被引:16
|
作者
Amrallah, Amr [1 ,2 ]
Mohamed, Ehab Mahmoud [3 ,4 ]
Tran, Gia Khanh [1 ,2 ]
Sakaguchi, Kei [1 ,2 ]
机构
[1] Tokyo Inst Technol, Sch Engn, Dept Elect & Elect Engn, 2-12-1 Ookayama,Meguro Ku, Tokyo 1528550, Japan
[2] Tokyo Inst Technol, Acad Super Smart Soc, 2-12-1 Ookayama,Meguro Ku, Tokyo 1528550, Japan
[3] Prince Sattam BinAbdulaziz Univ, Coll Engn Wadi Addawasir, Dept Elect Engn, Fac Engn, Wadi Addawasir 11991, Saudi Arabia
[4] Aswan Univ, Fac Engn, Dept Elect Engn, Aswan 81542, Egypt
关键词
unmanned aerial vehicle; trajectory optimization; reinforcement learning; multi-armed bandit; cost subsidy; post-disaster; WIRELESS NETWORKS; DESIGN; DEPLOYMENT;
D O I
10.3390/s23031402
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Over the past few years, with the rapid increase in the number of natural disasters, the need to provide smart emergency wireless communication services has become crucial. Unmanned aerial Vehicles (UAVs) have gained much attention as promising candidates due to their unprecedented capabilities and broad flexibility. In this paper, we investigate a UAV-based emergency wireless communication network for a post-disaster area. Our optimization problem aims to optimize the UAV's flight trajectory to maximize the number of visited ground users during the flight period. Then, a dual cost-aware multi-armed bandit algorithm is adopted to tackle this problem under the limited available energy for both the UAV and ground users. Simulation results show that the proposed algorithm could solve the optimization problem and maximize the achievable throughput under these energy constraints.
引用
收藏
页数:19
相关论文
共 26 条
  • [21] Trajectory Design for UAV-to-Ground Communication With Energy Optimization Using Genetic Algorithm for Agriculture Application
    Indu
    Singh, Rishi Pal
    Choudhary, Harji Ram
    Dubey, Anil Kumar
    IEEE SENSORS JOURNAL, 2021, 21 (16) : 17548 - 17555
  • [22] Energy-Aware Healthcare System for Wireless Body Region Networks in IoT Environment Using the Whale Optimization Algorithm
    Li, Xiao-ru
    Jiang, He
    WIRELESS PERSONAL COMMUNICATIONS, 2022, 126 (03) : 2101 - 2117
  • [23] Energy-Aware Microservice-Based SaaS Deployment in a Cloud Data Center Using Hybrid Particle Swarm Optimization
    Alzahrani, A.
    Tang, M.
    IEEE ACCESS, 2024, 12 : 140884 - 140899
  • [24] Energy-aware remanufacturing process planning and scheduling problem using reinforcement learning-based particle swarm optimization algorithm
    Wang, Jun
    Zheng, Handong
    Zhao, Shuangyao
    Zhang, Qiang
    JOURNAL OF CLEANER PRODUCTION, 2024, 476
  • [25] EETO-GA: Energy Efficient Trajectory Optimization of UAV-IoT Collaborative System Using Genetic Algorithm
    Rahman, M. M. Hafizur
    Al-Naeem, Mohammed
    Banerjee, Anuradha
    Sufian, Abu
    APPLIED SCIENCES-BASEL, 2023, 13 (04):
  • [26] Ellipsoidal Trajectory Optimization for Minimizing Latency and Data Transmission Energy in UAV-Assisted MEC Using Deep Reinforcement Learning
    Sadia, Rabeya
    Akter, Shathee
    Yoon, Seokhoon
    Forestiero, Agostino
    APPLIED SCIENCES-BASEL, 2023, 13 (22):