TopoDT: Digital Twin-Assisted UAV Topology Optimization for Targets Tracking
Zhou, Longyu Leng, Supeng Li, Zonghang Quek, Tony Q.S.
Zhou, Longyu
Leng, Supeng
Li, Zonghang
Quek, Tony Q.S.
Supervisor
Department
Machine Learning
Embargo End Date
Type
Conference proceeding
Date
2025
License
Language
English
Collections
Research Projects
Organizational Units
Journal Issue
Abstract
Unmanned Aerial Vehicles (UAVs) have been an attractive device to serve target tracking scenarios, such as hit- and-run tracking and border patrol. Nonetheless, it is difficult to implement real-time UAV topology optimization due to communication resources of UAVs and random moving speeds of targets. To address the problem, we propose a Digital Twins-assisted topology optimization framework (TopoDT). We formulate a UAV topology optimization model based on Lyapunov theory in the framework. The model is decoupled into two subproblems using our proposed TopoDT topology optimization algorithm. The DT model can allow UAVs to implement neighbor selection to construct and optimize small-scale local topologies for tracking low-speed moving targets. In addition, it allows UAVs to construct large-scale global topologies for tracking high-speed moving targets based on trajectory derivation. The system simulation results demonstrate that our solution reduces the end-to-end latency by 63.0% while decreasing the hop counts by 50% compared to state-of-the-art benchmarks.
Citation
L. Zhou, S. Leng, Z. Li and T. Q. S. Quek, "TopoDT: Digital Twin-Assisted UAV Topology Optimization for Targets Tracking," 2025 International Wireless Communications and Mobile Computing (IWCMC), Abu Dhabi, United Arab Emirates, 2025, pp. 79-84, doi: 10.1109/IWCMC65282.2025.11059545.
Source
24th International Wireless Communications and Mobile Computing Conference, IWCMC 2025
Conference
21st IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2025
Keywords
Digital twins, large-scale UAV topology, small-scale UAV topology, UAV topology optimization
Subjects
Source
21st IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2025
Publisher
IEEE