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Computer Engineering ›› 2026, Vol. 52 ›› Issue (4): 358-365. doi: 10.19678/j.issn.1000-3428.0069884

• Next-Generation Networks and Edge Computing • Previous Articles     Next Articles

AoI━Energy Tradeoff Scheme for UAV-Assisted Wireless Sensor Network Data Collection

TIAN Hailong1, JIA Xiangdong1,2,*(), ZHANG Xingyuan1, CHANG Heng1   

  1. 1. College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, Gansu, China
    2. Jiangsu Key Laboratory of Wireless Communications, Nanjing University of Posts and Telecommunications, Nanjing 210003, Jiangsu, China
  • Received:2024-05-21 Revised:2024-08-06 Online:2026-04-15 Published:2024-10-16
  • Contact: JIA Xiangdong

无人机辅助无线传感器网络数据采集的信息年龄-能量权衡方案

田海龙1, 贾向东1,2,*(), 张兴元1, 常恒1   

  1. 1. 西北师范大学计算机科学与工程学院, 甘肃 兰州 730070
    2. 南京邮电大学江苏省无线通信重点实验室, 江苏 南京 210003
  • 通讯作者: 贾向东
  • 作者简介:

    田海龙, 男, 硕士研究生, 主研方向为无线通信

    贾向东(通信作者), 教授、博士

    张兴元, 硕士研究生

    常恒, 硕士研究生

  • 基金资助:
    国家自然科学基金(62261048)

Abstract:

With advances in communication technology, the Internet of Things (IoT) has played an increasingly important role in real life, and the application of Unmanned Aerial Vehicle (UAV) communication in the IoT has been widely studied. UAVs are used as mobile data collectors to collect data from Sensor Nodes (SNs) in a WSN. The Age of Information (AoI) is introduced as an index for evaluating network performance. This paper proposes a data collection scheme based on UAV trajectory design and a scheduling strategy for SNs. Based on this scheme, a weighted minimization model is constructed to minimize the weighted sum of the Average AoI (AAoI) and energy consumption of the SNs by optimizing the trajectory of the UAV, the scheduling of the SNs, and the transmitting power. This mixed-integer nonlinear problem is usually difficult to solve directly. Therefore, the path discretization method is first used to discretize multiple continuous variables. Subsequently, a joint optimization algorithm based on Block Coordinate Descent (BCD) and Successive Convex Approximation (SCA) is proposed to obtain a local optimal solution that satisfies the KKT condition. The simulation results show an effective balance between the AoI and the energy consumption of the SNs, demonstrating the feasibility of the proposed scheme.

Key words: Wireless Sensor Network (WSN), Unmanned Aerial Vehicle (UAV), data collection, Age of Information (AoI), convex optimization

摘要:

随着通信技术的发展, 物联网(IoT)在现实生活中发挥着越来越重要的作用, 无人机(UAV)通信在IoT中的应用也得到了广泛研究。UAV作为移动数据收集器, 用于采集无线传感器网络(WSN)中感知节点(SN)的数据。引入信息年龄(AoI)作为评价网络性能的指标, 提出一种基于UAV轨迹设计和SN调度策略的数据采集方案。基于该方案, 构建了平均AoI(AAoI)和SN能耗加权最小化模型, 通过优化UAV的轨迹、SN的调度以及发射功率, 最小化系统AAoI和能耗的加权和, 该问题为混合整数非线性问题, 通常难以直接求解。因此, 首先利用路径离散化方法将多个连续的变量离散化, 然后提出基于块坐标下降法(BCD)和连续凸逼近(SCA)的联合优化算法, 得到满足KKT条件的局部最优解。从仿真结果可以看出, AoI和SN能耗得到有效平衡, 表明了所提方案的可行性。

关键词: 无线传感器网络, 无人机, 数据采集, 信息年龄, 凸优化