Multi-Blockchain Based Data Trading Markets With Novel Pricing Mechanisms

Juanjuan Li; Junqing Li; Xiao Wang; Rui Qin; Yong Yuan; Fei-Yue Wang

doi:10.1109/JAS.2023.123963

Volume 10 Issue 12

Dec. 2023

IEEE/CAA Journal of Automatica Sinica

JCR Impact Factor: 11.8, Top 4% (SCI Q1)

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2023 > 10(12): 2222-2232

J. Li, J. Li, X. Wang, R. Qin, Y. Yuan, and F.-Y. Wang, “Multi-blockchain based data trading markets with novel pricing mechanisms,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 12, pp. 2222–2232, Dec. 2023. doi: 10.1109/JAS.2023.123963

Citation:

J. Li, J. Li, X. Wang, R. Qin, Y. Yuan, and F.-Y. Wang, “Multi-blockchain based data trading markets with novel pricing mechanisms,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 12, pp. 2222–2232, Dec. 2023. doi: 10.1109/JAS.2023.123963

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Multi-Blockchain Based Data Trading Markets With Novel Pricing Mechanisms

doi: 10.1109/JAS.2023.123963

Funds: This work was partially supported by the Science and Technology Development Fund, Macau SAR (0050/2020/A1) and the National Natural Science Foundation of China (62103411, 72171230)

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Author Bio:
Juanjuan Li (Member, IEEE) received the M.S. degree in economics from Renmin University of China in 2010, and the Ph.D. degree in control science and engineering from Beijing Institute of Technology in 2021. She is currently an Associate Professor with State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences. Her research interests include blockchain, DAO and parallel management

Junqing Li is currently a Ph.D. candidate in computer application technology at the College of Computer Science and Engineering, Shandong University of Science and Technology. His research interest includes blockchain intelligence

Xiao Wang (Senior Member, IEEE) received the B.E. degree in network engineering from Dalian University of Technology in 2011, and the Ph.D. degree in social computing from the University of Chinese Academy of Sciences in 2016. She is currently a Professor with the School of Artificial Intelligence, Anhui University, and the President of the Qingdao Academy of Intelligent Industries. Her research interests include social network analysis, social transportation, cyber movement organizations, and multiagent modeling

Rui Qin (Member, IEEE) received the Ph.D. degree in computer application technology from the University of Chinese Academy of Sciences in 2016. She is currently an Associate Professor with State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences. Her research interests include blockchain, DAO, parallel management and social computing

Yong Yuan (Senior Member, IEEE) received the B.S., M.S. and Ph.D. degrees in computer software and theory from the Shandong University of Science and Technology, in 2001, 2004, and 2008, respectively. He is currently a Professor with the School of Mathematics, Renmin University of China. His current research interests include blockchain, cryptocurrency, and smart contracts. He has authored over 150 articles published in academic journals and conferences. He is also an Associate Editor of the IEEE Transactions on Computational Social Systems and Acta Automatica Sinica. He is the Chair of the IEEE Council on RFID Technical Committee on Blockchain, the Co-Chair of the IEEE SMC Technical Committee on Blockchain, and the Director of the Chinese Association of Automation Technical Committee of Blockchain. He is the Secretary General of the IEEE SMC Technical Committee on Social Computing and Social Intelligence, the Vice Chair of the IFAC Technical Committee on Economic, Business, and Financial Systems (TC 9.1). He is also the Vice Director and the Secretary General of the Chinese Academy of Management Technical Committee on Parallel Management

Fei-Yue Wang (Fellow, IEEE) received the Ph.D. degree in computer and systems engineering from the Rensselaer Polytechnic Institute, USA in 1990. He joined The University of Arizona, USA in 1990 and became a Professor and the Director of the Robotics and Automation Laboratory and the Program in Advanced Research for Complex Systems. In 1999, he founded the Intelligent Control and Systems Engineering Center at the Institute of Automation, Chinese Academy of Sciences (CAS), under the support of the Outstanding Chinese Talents Program from the State Planning Council, and in 2002, was appointed as the Director of the Key Laboratory of Complex Systems and Intelligence Science, CAS, and Vice President of Institute of Automation, CAS in 2006. He found CAS Center for Social Computing and Parallel Management in 2008, and became the State Specially Appointed Expert and the Founding Director of the State Key Laboratory for Management and Control of Complex Systems in 2011. His research interests include parallel intelligence, social computing, and knowledge automation. He is a Fellow of INCOSE, IFAC, ASME, and AAAS. In 2007, he received the National Prize in Natural Sciences of China, numerous best papers awards from IEEE Transactions, and became an Outstanding Scientist of ACM for his work in intelligent control and social computing. He received the IEEE ITS Outstanding Application and Research Awards in 2009, 2011, and 2015, respectively, the IEEE SMC Norbert Wiener Award in 2014, and became the IFAC Pavel J. Nowacki Distinguished Lecturer in 2021. Since 1997, he has been serving as the General or Program Chair of over 30 IEEE, INFORMS, IFAC, ACM, and ASME conferences. He was the President of the IEEE ITS Society from 2005 to 2007, the IEEE Council of RFID from 2019 to 2021, the Chinese Association for Science and Technology, USA, in 2005, the American Zhu Kezhen Education Foundation from 2007 to 2008, the Vice President of the ACM China Council from 2010 to 2011, the Vice President and the Secretary General of the Chinese Association of Automation from 2008 to 2018, the Vice President of IEEE Systems, Man, and Cybernetics Society from 2019 to 2021. He was the Founding Editor-in-Chief (EiC) of the International Journal of Intelligent Control and Systems from 1995 to 2000, IEEE ITS Magazine from 2006 to 2007, IEEE/CAA Journal of Automatica Sinica from 2014 to 2017, China’s Journal of Command and Control from 2015 to 2021, and China’s Journal of Intelligent Science and Technology from 2019 to 2021. He was the EiC of the IEEE Intelligent Systems from 2009 to 2012, IEEE Transactions on Intelligent Transportation Systems from 2009 to 2016, IEEE Transactions on Computational Social Systems from 2017 to 2020. Currently, he is the President of CAA’s Supervision Council, and the EiC of IEEE Trans. on Intelligent Vehicles
Corresponding author: Juanjuan Li, e-mail: juanjuan.li@ia.ac.cn; Fei-Yue Wang, e-mail: feiyue.wang@ia.ac.cn
Received Date: 2023-07-11
Revised Date: 2023-09-06
Accepted Date: 2023-09-11

Available Online: 2023-10-12

Abstract

Abstract

In the era of big data, there is an urgent need to establish data trading markets for effectively releasing the tremendous value of the drastically explosive data. Data security and data pricing, however, are still widely regarded as major challenges in this respect, which motivate this research on the novel multi-blockchain based framework for data trading markets and their associated pricing mechanisms. In this context, data recording and trading are conducted separately within two separate blockchains: the data blockchain (DChain) and the value blockchain (VChain). This enables the establishment of two-layer data trading markets to manage initial data trading in the primary market and subsequent data resales in the secondary market. Moreover, pricing mechanisms are then proposed to protect these markets against strategic trading behaviors and balance the payoffs of both suppliers and users. Specifically, in regular data trading on VChain-S2D, two auction models are employed according to the demand scale, for dealing with users’ strategic bidding. The incentive-compatible Vickrey-Clarke-Groves (VCG) model is deployed to the low-demand trading scenario, while the nearly incentive-compatible monopolistic price (MP) model is utilized for the high-demand trading scenario. With temporary data trading on VChain-D2S, a reverse auction mechanism namely two-stage obscure selection (TSOS) is designed to regulate both suppliers’ quoting and users’ valuation strategies. Furthermore, experiments are carried out to demonstrate the strength of this research in enhancing data security and trading efficiency.
- Auction,
- data trading markets,
- multi-blockchain,
- pricing mechanisms

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References

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Establish multi-blockchain based data trading markets to enhance security and efficiency
Use the VCG and MP auction mechanism to induce truthful bidding in regular data trading
Design the TSOS mechanism to regulate strategic trading behaviors in temporary data trading

Multi-Blockchain Based Data Trading Markets With Novel Pricing Mechanisms

doi: 10.1109/JAS.2023.123963

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通讯作者: 陈斌, bchen63@163.com

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