Computing power networks for unmanned aerial vehicles: a hierarchical resources trading market✩

Xiaofei Wang; Hui Deng; Chao Qiu; Zheyuan Chen; Tao Luo; Zhao Ming

doi:10.1016/j.dcan.2024.12.002

›› 2026, Vol. 12 ›› Issue (4) :584 -593. DOI: 10.1016/j.dcan.2024.12.002

research-article

Computing power networks for unmanned aerial vehicles: a hierarchical resources trading market^✩

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^a College of Intelligence and Computing, Tianjin University , Tianjin 300072, China

^b China Telecom Digital City Technology Co., Ltd , Xiongan 210019, China

^c The Centre for Wireless Communications, University of Oulu , Oulu, Finland

^* E-mail addresses: xiaofeiwang@tju.edu.cn (X. Wang),

fjdenghui1@tju.edu.cn (H. Deng),

chao.qiu@tju.edu.cn (C. Qiu),

chenzheyuan@tju.edu.cn (Z. Chen),

luo_tao@tju.edu.cn (T. Luo),

zhao.ming@oulu.fi (Z. Ming).

Xiaofei Wang (Senior Member, IEEE) received the BS degree from the Huazhong University of Science and Technology, China, and the MS and PhD degrees from Seoul National University, Seoul, South Korea. He was a postdoctoral fellow with The University of British Columbia, Vancouver, BC, Canada, from 2014 to 2016. He is currently a professor with the College of Intelligence and Computing, Tianjin University, Tianjin, China. He has authored or coauthored more than 200 technical papers in IEEE Journal on Selected Areas in Communications, IEEE Transactions on Cloud Computing, IEEE/ACM Transactions on Networking, IEEE Transactions on Wireless Communications, IEEE Internet of Things Journal, COMST, IEEE Transactions on Multimedia, INFOCOM, and ICDCS, in his research interests which include edge computing, edge intelligence, and edge systems. He was the recipient of the best paper awards of IEEE ICC, ICPADS, in 2017, "IEEE ComSoc Fred W. Ellersick Prize", and in 2022, "IEEE ComSoc Asia-Pacific Outstanding Paper Award".

Hui Deng, a professor-level senior engineer, received the BS and MS degrees from Fuzhou University, Fuzhou, China. He is currently pursuing the PhD degree in computer application technology with Tianjin University, Tianjin, China, and is also with China Telecom Digital City Technology Co., Ltd. His research interests include intelligent transportation systems, connected and automated vehicles, traffic simulation and cooperative control, wireless power transfer, electronic system optimization, and AI-driven sensing and computing for intelligent vehicles. He has led and participated in several national research projects, including the Xiong’an New Area Science and Technology Innovation Project on multi-granularity traffic system simulation and cooperative control for narrow road dense-network scenarios, Project No. 2022XAGG0126, and the National Key Research and Development Program of China on coupled spatiotemporal vehicle-city interaction technologies, Grant No. 2022YFC3803704.

Chao Qiu (Member, IEEE) received the BS degree in communication engineering from China Agricultural University, in 2013, and the PhD degree in information and communication engineering from the Beijing University of Posts and Telecommunications, in 2019. She is currently an associate professor with the College of Intelligence and Computing, Tianjin University, China. From 2017 to 2018, she visited Carleton University, Ottawa, ON, Canada, as a Visiting Scholar. Her current research interests include edge computing, edge intelligence, and blockchain.

Zheyuan Chen received his B.S. degree in computer science and technology from Tianjin University, in 2021. He is currently working toward the M.S. degree in electronic information with the College of Intelligence and Computing. His current research interests include metaverse, blockchain, and computing power network.

Tao Luo received M.S. degree from the School of Precision Instrument and Opto-Electronics in 2006, and the Ph.D. degree from the School of Electronic Information Engineering, Tianjin University, Tianjin, China, in 2009. He is currently an Associate Professor with the School of Cyber security, Tianjin University. His research interests include Multimodal information security.

Zhao Ming (Student Member, IEEE) received the BS degree from the Wuhan University of Technology (WHUT), Wuhan, China, in 2018, and the ME degree from Chongqing University (CQU), Chongqing, China, in 2022. He is currently working toward the PhD degree with the Centre for Wireless Communications (CWC), University of Oulu, Oulu, Finland. His current research interests include network slicing, multi-access edge computing, anomaly detection, and AI/ML technologies and their combinations.

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Abstract

Unmanned Aerial Vehicles (UAVs) are increasingly deployed across military and civilian domains due to their operational flexibility, low maintenance costs, and high mobility. With the growing complexity of UAV applications and tasks, robust support from computing power networks is essential. These networks, acting as resource integration paradigms, furnish UAVs with pooled resources to tackle extensive computational demands. In this paper, we develop a framework for trading computing power resources, modeling the transaction process through a three-stage Stackelberg game to facilitate sequential decision-making. We theoretically demonstrate the existence of a Nash equilibrium and introduce a Dynamic Game Reinforcement algorithm to identify optimal strategies. Our experimental results affirm the framework’s efficacy and the superior performance of our algorithm. Additionally, we explore how variables like UAV quantity and network congestion influence the market dynamics of the computing power network.

Keywords

UAVs / Cloud computing / Computing power network / Resource trading / Stackelberg game

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Xiaofei Wang, Hui Deng, Chao Qiu, Zheyuan Chen, Tao Luo, Zhao Ming. Computing power networks for unmanned aerial vehicles: a hierarchical resources trading market^✩. , 2026, 12 (4) : 584-593 DOI:10.1016/j.dcan.2024.12.002

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CRediT authorship contribution statement

Xiaofei Wang: Methodology, Conceptualization. Hui Deng: Resources. Chao Qiu: Writing -- review & editing, Writing -- original draft, Methodology, Formal analysis, Conceptualization. Zheyuan Chen: Writing -- original draft, Visualization, Validation, Formal analysis. Tao Luo: Supervision, Methodology. Zhao Ming: Methodology, Conceptualization.

Declaration of competing interest

In this paper, no conflict exits in the submission of this manuscript, and the manuscript is approved by all authors for publication. I would like to declare on behalf of my co-authors that the work has not been published previously, and not been under consideration for publication elsewhere.

Acknowledgements

This research work is supported by Xiong’an New Area Science and Technology Innovation Special Project (Research on Multi granularity Traffic System Simulation and Collaborative Control Technology for Narrow Road and Dense Network in Xiong’an New Area) No. 2022XAGG0126. The research work is also funded by the science and technology project of SGCC (State Grid Corporation of China): Research on Key Technologies and Applications of Intelligent Edge Computing for Transmission Line Defect Sensing (5700-202318309A-1-1-ZN).

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