多无人机辅助物联网中信息年龄最小化的数据采集与分发优化算法

王梓萌; 朱琦

doi:10.11959/j.issn.1000-0801.DXKX260155

Chinese

您当前的位置：

首页 >

文章列表页 >

多无人机辅助物联网中信息年龄最小化的数据采集与分发优化算法

更新时间：2026-06-23

- 多无人机辅助物联网中信息年龄最小化的数据采集与分发优化算法
- Optimization algorithm for data collection and dissemination with age of information minimization in multi-uav-assisted iot
- 电信科学 2026年
- 作者机构：
  
  1.南京邮电大学江苏省无线通信重点实验室，江苏南京210003
  2.南京邮电大学教育部泛在网络健康服务系统工程研究中心，江苏南京210003
- 作者简介：
  
  王梓萌女，2002年生，辽宁海城人。南京邮电大学通信与信息工程学院硕士研究生，主要研究方向为无线通信。
  朱琦，zhuqi@njupt.edu.cn
- 基金信息：
  
  国家自然科学基金资助项目(92367302);江苏省重点研发计划(BE2022068-2)
- DOI：10.11959/j.issn.1000-0801.DXKX260155
  中图分类号： TN929.5
- 收稿：2026-03-09，
  
  修回：2026-04-28，
  
  录用：2026-06-23，
- 稿件说明：
移动端阅览
王梓萌, 朱琦. 多无人机辅助物联网中信息年龄最小化的数据采集与分发优化算法[J/OL]. 电信科学, 2026.

WANG Zimeng, ZHU Qi. Optimization algorithm for data collection and dissemination with age of information minimization in multi-uav-assisted iot[J/OL]. Telecommunications Science, 2026.
王梓萌, 朱琦. 多无人机辅助物联网中信息年龄最小化的数据采集与分发优化算法[J/OL]. 电信科学, 2026. DOI： 10.11959/j.issn.1000-0801.DXKX260155.

WANG Zimeng, ZHU Qi. Optimization algorithm for data collection and dissemination with age of information minimization in multi-uav-assisted iot[J/OL]. Telecommunications Science, 2026. DOI： 10.11959/j.issn.1000-0801.DXKX260155.

摘要

随着物联网技术的普及，海量传感器数据需要被高效处理，无人机凭借其灵活部署与移动通信的优势，突破了固定设施的局限，实现了对目标区域数据的快速采集与分发。针对无人机辅助物联网中数据采集与分发的信息新鲜度问题，本文提出了一种基于信息年龄的无人机数据采集和分发的优化算法。在无线传感器节点的通信距离、无人机数量和信噪比阈值的限制下，建立了用户获得数据的平均AoI最小化优化问题。将该问题分解为成簇数目、区域划分以及无人机轨迹三个优化子问题，采用改进的K-means聚类算法对区域内的传感器节点进行成簇，然后根据簇首的位置采用基于几何质心距离的区域划分算法将整个区域分成多个子区域，每个无人机负责采集一个子区域内的数据，采用基于固定起点和终点的2-opt优化算法获得每个无人机的飞行轨迹。然后选择一架能量最优的无人机，其他无人机以频分多址的方式与其进行数据共享，再由该无人机以飞行和悬停混合方式将数据分发给用户，通过预测飞行时可以分发的数据量以获得无人机在关联用户上方的停留时间。仿真结果表明，本文提出的优化算法可以有效减少平均AoI，有效保障数据的新鲜度。

Abstract

With the widespread adoption of Internet of Things (IoT) technology

massive amounts of sensor data

require efficient processing. Unmanned Aerial Vehicles (UAVs)

leveraging their flexible deployment and mobile communication advantages

break through the limitations of fixed infrastructure

enabling rapid data collection and distribution in target areas. To address the issue of information freshness in UAV-assisted IoT data collection and distribution

this paper proposes an optimization algorithm for UAV data collection and distribution based on Information Age. Under the constraints of wireless sensor node communication range

UAV quantity

and signal-to-noise ratio threshold

an optimization problem is formulated to minimize the average Age of Information (AoI) for users receiving data. This problem is decomposed into three sub-problems: cluster number optimization

area partitioning

and UAV trajectory planning. An improved K-means clustering algorithm is employed to cluster the sensor nodes within the area. Then

based on the positions of the cluster heads

a region partitioning algorithm using geometric centroid distance is applied to divide the entire area into multiple sub-regions

with each UAV responsible for collecting data from one sub-region. A 2-opt optimization algorithm with fixed start and end points is utilized to obtain the flight trajectory for each UAV. Subsequently

the UAV with optimal energy efficiency is selected. Other UAVs share data with it using Frequency Division Multiple Access (FDMA). This selected UAV then distributes the data to users through a hybrid strategy of flying and hovering

predicting the amount of data that can be distributed during flight to determine the hovering time above associated users. Simulation results demonstrate that the proposed optimization algorithm effectively reduces the average AoI

thereby ensuring data freshness.

关键词

Keywords

references

FANG Z X . Optimized Coverage Deployment Strategy for a Network of UAVs Monitoring a Disaster Area on an Uneven Terrain [C ] // 2024 16th International Conference on Computer and Automation Engineering (ICCAE) . Melbourne, Australia . IEEE , 2024 : 583 - 587 .

LIN Y , and LEE R . Application of multi-band networking and UAV in natural environment protection and disaster prevention [C ] // 2019 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE) , Yunlin, Taiwan. IEEE , 2019 :176- 178 ,

TONG S Y , LIU Y , Mišić J , et al . Joint Task Offloading and Resource Allocation for Fog-Based Intelligent Transportation Systems: A UAV-Enabled Multi-Hop Collaboration Paradigm [J ] . IEEE Transactions on Intelligent Transportation Systems , 2023 , 24 ( 11 ): 12933 - 12948 .

LI M , LIU X , and WANG H . Completion Time Minimization Considering GNs’ Energy for UAV-Assisted Data Collection [J ] . IEEE Wireless Communications Letters , 2023 , 12 ( 12 ): 2128 - 2132

CHAPNEYIS A , and BULUT E . Delay Optimal UAV Trajectory Planning for Secure Data Collection from Mobile IoT Networks [C ] // 2023 IEEE International Conference on Industrial Technology(ICIT) , Orlando, FL, USA . IEEE , 2023 : 1 - 4 .

SHEN L F , WANG N , ZHANG D , et al . Energy-Aware Dynamic Trajectory Planning for UAV-Enabled Data Collection in mMTC Networks [J ] . IEEE Transactions on Green Communications and Networking , 2022 , 6 ( 4 ): 1957 - 1971 .

FU Q Y , JIA R H , LIN F L , et al . Collection Point Matters in Time–Energy Tradeoff for UAV-Enabled Data Collection of IoT Devices [J ] . IEEE Internet of Things Journal , 2024 , 11 ( 19 ): 31492 - 31506 .

LI M , HE S S , and LI H . Minimizing Mission Completion Time of UAVs by Jointly Optimizing the Flight and Data Collection Trajectory in UAV-Enabled WSNs [J ] . IEEE Internet of Things Journal , 2022 , 9 ( 15 ): 13498 - 13510 .

NIE G F , MA T , ZHANG Z , et al . Coarse Closed-Loop Trajectory Design of Multiple UAVs for Parallel Data Collection [J ] . IEEE Transactions on Vehicular Technology , 2023 , 72 ( 3 ): 4026 - 4039 .

SHEN S , YANG K , WANG K Z , et al . Number and Operation Time Minimization for Multi-UAV-Enabled Data Collection System With Time Windows [J ] . IEEE Internet of Things Journal , 2022 , 9 ( 12 ): 10149 - 10161 .

KAUL S , YATES R and GRUTESER M . Real-time status: How often should one update [C ] // Proceedings - IEEE INFOCOM , Orlando, FL, USA . IEEE , 2012 : 2731 - 2735 .

ZHOU X Y , and ZHU i . Optimization Algorithm for AoI-Based UAV-Assisted Data Collection [J ] . International Journal of Distributed Sensor Networks , 2024 , 25 ( 12 ): 1 - 15

FU X W , PAN Q S , and HUANG X . AoI-Energy-Aware Collaborative Data Collection in UAV-Enabled Wireless Powered Sensor Networks [J ] . IEEE Sensors Journal , 2023 , 23 ( 23 ): 31303 - 31324 .

HU H M , XIONG K , QU G , et al . AoI-Minimal Trajectory Planning and Data Collection in UAV-Assisted Wireless Powered IoT Networks [J ] . IEEE Internet Of Things Journal , 2021 , 8 ( 2 ): 1211 - 1223 .

WU T H , LIU J F , LIU J , et al . A Novel AI-Based Framework for AoI-Optimal Trajectory Planning in UAV-Assisted Wireless Sensor Networks [J ] . IEEE Transactions on Wireless Communications , 2022 , 21 ( 4 ): 2462 - 2475 .

ZHANG X H , LU W R , SHEN Y Y , et al . Average AoI Minimization in UAV-Assisted IoT Backscatter Communication Systems with Updated Information [C ] // 2021 IEEE SmartWorld , Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/IOP/SCI) , Atlanta,GA,USA . IEEE , 2021 : 132 - 130 .

GAO X X , ZHU X M and ZHAI L B . AoI-Sensitive Data Collection in Multi-UAV-Assisted Wireless Sensor Networks [J ] . IEEE Transactions on Wireless Communications , 2023 , 22 ( 8 ): 5185 - 5197 .

LIU C T , GUO Y , LI N , et al . AoI-Minimal Task Assignment and Trajectory Optimization in Multi-UAV-Assisted IoT Networks [J ] . IEEE Internet Of Things Journal , 2022 , 9 ( 21 ): 21777 - 21791

DENG C and FU X W . Low-AoI Data Collection in UAV-Aided Wireless-Powered IoT Based on Aerial Collaborative Relay [J ] . IEEE Sensors Journal , 2024 , 24 ( 20 ): 33506 - 33521 .

AKRAM A , SITHAMPARANATHAN K and SIMON L . Optimal LAP Altitude for Maximum Coverage [J ] . IEEE Wireless Communications Letters , 2014 , 3 ( 6 ): 569 - 572 .

ZHEN C Y , XU J , and ZHANG R . Energy minimization for wireless communication with rotary-wing UAV [J ] . IEEE Trans Wireless Commun , 2019 , 18 ( 4 ): 2329 - 2345 .

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于区块链的频谱共享算法

面向智能化变电站的数字孪生技术应用

低空3.5 GHz双载波网络覆盖解决方案研究

基于“通算存”资源协同的无人机链路异常监测方案研究

空中可重构智能表面辅助的全双工无人机安全通信