Keep Fresh Digital Twins In UAV-Assisted IoT Networks By Exploiting Data Correlations

Author

• Qunli Shen
• Jing Li
• Jian Peng
• Zichuan Xu
• Cheng Zhao
• Pan Zhou
• Weifa Liang
• Xiaohua Jia
• Sajal K. Das, Missouri University of Science and TechnologyFollow
• Wenzheng Xu

Abstract

In this paper, we study the Digital Twin (DT) synchronization in Internet of Things (IoT), in which multiple UAVs periodically collect data from IoT devices, and the collected data is used for updating the corresponding DTs of IoT devices. It is very important to minimize the DT ages of IoT devices, as the DT ages measure the synchronization degree between DTs and their real-world IoT devices, and the DT ages are critical for various downstream tasks in the DT system. Unlike most existing studies that did not consider data correlations among IoT devices, we focus on that UAVs can collect non-redundant data, thereby reducing the data collection time. Then, more IoT devices can upload their sensing data for synchronizing with their DTs per time unit, and the DT ages of more IoT devices will decrease. In this paper, we study a novel DT age minimization problem, which is to find tours for K available energy-constrained UAVs to collect spatio-temporally correlated data from IoT devices, such that the accumulative reduced DT age of all IoT devices is maximized after the data collection. We propose a novel 0.18-approximation algorithm for the problem. Both experiments based on a real testbed and simulations show that the accumulative reduced DT age by the algorithm is up to 35% larger than existing algorithms. In addition, the empirical approximation ratio of the proposed algorithm is between 0.5 and 0.94, which is much larger than its worst-case approximation ratio 0.18.

Recommended Citation

Q. Shen and J. Li and J. Peng and Z. Xu and C. Zhao and P. Zhou and W. Liang and X. Jia and S. K. Das and W. Xu, "Keep Fresh Digital Twins In UAV-Assisted IoT Networks By Exploiting Data Correlations," Proceedings International Conference on Distributed Computing Systems, pp. 120 - 130, Institute of Electrical and Electronics Engineers, Jan 2026.

The definitive version is available at https://doi.org/10.1109/2575-8411.2026.00019

Department(s)

Computer Science

Comments

Sichuan Provincial Science and Technology Support Program, Grant 22ZDYF3599

Keywords and Phrases

approximation algorithm; data collection; Digital twin; UAVs

International Standard Serial Number (ISSN)

2575-8411; 1063-6927

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2026 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

01 Jan 2026