Cooperative Data Collection With Multiple UAVs for Information Freshness in the Internet of Things

被引:22
|
作者
Wang, Xijun [1 ]
Yi, Mengjie [2 ]
Liu, Juan [3 ]
Zhang, Yan [4 ]
Wang, Meng [5 ]
Bai, Bo [5 ]
机构
[1] Sun Yat Sen Univ, Sch Elect & Informat Technol, Guangzhou 510006, Peoples R China
[2] Xidian Univ, Sch Cyber Engn, Xian 710071, Peoples R China
[3] Ningbo Univ, Sch Elect Engn & Comp Sci, Ningbo 315211, Zhejiang, Peoples R China
[4] Xidian Univ, Informat Sci Inst, State Key Lab Integrated Serv Networks, Xian 710071, Shaanxi, Peoples R China
[5] Huawei Technol Co Ltd, Theory Lab, Labs 2012, Cent Res Inst, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Trajectory; Data collection; Autonomous aerial vehicles; Internet of Things; Energy consumption; Scheduling; Training; Age of information; deep reinforcement learning; unmanned aerial vehicle; ENERGY-EFFICIENT; TRAJECTORY DESIGN; FAIR COMMUNICATION; IOT NETWORKS; AGE; MINIMIZATION;
D O I
10.1109/TCOMM.2023.3255240
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Maintaining the freshness of information in the Internet of Things (IoT) is a critical yet challenging problem. In this paper, we study cooperative data collection using multiple Unmanned Aerial Vehicles (UAVs) with the objective of minimizing the total average Age of Information (AoI). We consider various constraints of the UAVs, including kinematic, energy, trajectory, and collision avoidance, in order to optimize the data collection process. Specifically, each UAV, which has limited on-board energy, takes off from its initial location and flies over sensor nodes to collect update packets in cooperation with the other UAVs. The UAVs must land at their final destinations with non-negative residual energy after the specified time duration to ensure they have enough energy to complete their missions. It is crucial to design the trajectories of the UAVs and the transmission scheduling of the sensor nodes to enhance information freshness. We model the multi-UAV data collection problem as a Decentralized Partially Observable Markov Decision Process (Dec-POMDP), as each UAV is unaware of the dynamics of the environment and can only observe a part of the sensors. To address the challenges of this problem, we propose a multi-agent Deep Reinforcement Learning (DRL)-based algorithm with centralized learning and decentralized execution. In addition to the reward shaping, we use action masks to filter out invalid actions and ensure that the constraints are met. Simulation results demonstrate that the proposed algorithms can significantly reduce the total average AoI compared to the baseline algorithms, and the use of the action mask method can improve the convergence speed of the proposed algorithm.
引用
收藏
页码:2740 / 2755
页数:16
相关论文
共 50 条
  • [21] Collaborative Online Caching with Freshness in the Internet of Things
    Zhao, Xu
    Zhu, Qi
    2020 12TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING (WCSP), 2020, : 916 - 921
  • [22] Information Freshness-Guaranteed and Energy-Efficient Data Generation Control System in Energy Harvesting Internet of Things
    Ko, Haneul
    Lee, Hochan
    Kim, Taeyun
    Pack, Sangheon
    IEEE ACCESS, 2020, 8 (08): : 168711 - 168720
  • [23] Advances on data, information, and knowledge in the internet of things
    Sun, Yunchuan
    Bie, Rongfang
    Thomas, Peter
    Cheng, Xiuzhen
    PERSONAL AND UBIQUITOUS COMPUTING, 2014, 18 (08) : 1793 - 1795
  • [24] Advances on data, information, and knowledge in the internet of things
    Yunchuan Sun
    Rongfang Bie
    Peter Thomas
    Xiuzhen Cheng
    Personal and Ubiquitous Computing, 2014, 18 : 1793 - 1795
  • [25] Security Analysis of Cooperative Jamming in Internet of Things with Multiple Eavesdroppers
    Fan, Xin
    Huo, Yan
    2019 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2019,
  • [26] Dispatching and control information freshness guaranteed resource optimization in simplified power Internet of things
    Liao H.
    Jia Z.
    Zhou Z.
    Liu N.
    Wang F.
    Gan Z.
    Yao X.
    Tongxin Xuebao/Journal on Communications, 2022, 43 (07): : 203 - 214
  • [27] Channel Quality-Based Optimal Status Update for Information Freshness in Internet of Things
    Peng, Fuzhou
    Chen, Xiang
    Wang, Xijun
    ENTROPY, 2021, 23 (07)
  • [28] Cooperative Task Planning of Ground Relay with Nonholonomic Constraints in Mobile Internet of Things Based on UAVs
    Wang W.
    Peng L.
    Zhao J.-J.
    Chang C.-X.
    Huang X.-D.
    Tian L.-Q.
    Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2019, 47 (06): : 1251 - 1259
  • [29] Complete Coverage Path Planning for Data Collection with Multiple UAVs
    Chen, Yuhong
    Mou, Zhiyu
    Lin, Bo
    Zhang, Tengyu
    Gao, Feifei
    2024 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC 2024, 2024,
  • [30] Autonomous Navigation UAVs for Enhancing Information Freshness for Reconnaissance
    Xie, Chen
    Wu, Binbin
    Guo, Daoxing
    Chen, Xiao
    ELECTRONICS, 2024, 13 (07)