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Hybrid concurrency control protocol for data sharing among heterogeneous blockchains

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Abstract

With the development of information technology and cloud computing, data sharing has become an important part of scientific research. In traditional data sharing, data is stored on a third-party storage platform, which causes the owner to lose control of the data. As a result, there are issues of intentional data leakage and tampering by third parties, and the private information contained in the data may lead to more significant issues. Furthermore, data is frequently maintained on multiple storage platforms, posing significant hurdles in terms of enlisting multiple parties to engage in data sharing while maintaining consistency. In this work, we propose a new architecture for applying blockchains to data sharing and achieve efficient and reliable data sharing among heterogeneous blockchains. We design a new data sharing transaction mechanism based on the system architecture to protect the security of the raw data and the processing process. We also design and implement a hybrid concurrency control protocol to overcome issues caused by the large differences in blockchain performance in our system and to improve the success rate of data sharing transactions. We took Ethereum and Hyperledger Fabric as examples to conduct cross-blockchain data sharing experiments. The results show that our system achieves data sharing across heterogeneous blockchains with reasonable performance and has high scalability.

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Acknowledgements

The work was supported by the National Key Research and Development Program of China (Nos. 2020YFB1707900, 2021YFB2700700), the National Natural Science Foundation of China (NSFC) (Grant No. 62072035), the Open Research Projects of Zhejiang Lab (No. 2020KE0AB04), and CCF-Huawei Database System Innovation Research Plan (No. CCF-HuaweiDBIR2021007B). Ye Yuan is supported by the NSFC (Grant Nos. 61932004, 62225203, U21A20516). Xiaochun Yang is supported by the National Key Research and Development Program of China (No. 2020YFB1707900). Guoren Wang is supported by the NSFC (Nos. 61732003, U2001211).

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Authors and Affiliations

  1. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, 100029, China

    Tiezheng Guo, Zhiwei Zhang, Ye Yuan & Guoren Wang

  2. School of Computer Science and Engineering, Northeastern University, Shenyang, 110167, China

    Xiaochun Yang

Authors
  1. Tiezheng Guo
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  2. Zhiwei Zhang
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  3. Ye Yuan
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  4. Xiaochun Yang
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  5. Guoren Wang
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Corresponding author

Correspondence to Zhiwei Zhang.

Additional information

Tiezheng Guo received his BS degree from Dalian University of Technology (DUT), China in 2020. He is currently pursuing his MS degree in School of Computer Science and Technology, Beijing Institute of Technology (BIT), China. His current research interests include blockchain and distributed system.

Zhiwei Zhang received the BS degree from Renmin University of China in 2010, and PhD degree from the Chinese University of Hong Kong, China in 2014. He is currently a professor with the Beijing Institute of Technology (BIT), China. His research interests include federal learning, data pricing and transaction, distributed system, blockchain, and algorithm analysis.

Ye Yuan received the BS, MS and PhD degrees in Computer Science from Northeastern University, China in 2004, 2007, and 2011, respectively. He is currently a professor with the Beijing Institute of Technology (BIT), China. His research interests include graph databases, probabilistic databases, data privacy-preserving and cloud computing.

Xiaochun Yang received the BS, MS and PhD degrees in Computer Science from Northeastern University, China in 1995, 1998, and 2001, respectively. She is currently a professor in the Department of Computer Science at Northeastern University, China. Her research interests include big data management and analysis, data quality, and data privacy preserving.

Guoren Wang received the BS, MS, and PhD degrees from the Department of Computer Science, Northeastern University, China in 1988, 1991, and 1996, respectively. Currently, he is a professor with the Beijing Institute of Technology (BIT), China. His research interests include XML data management, query processing and optimization, bioinformatics, high dimensional indexing, parallel database systems, and cloud data management. He has published more than 100 research papers.

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Guo, T., Zhang, Z., Yuan, Y. et al. Hybrid concurrency control protocol for data sharing among heterogeneous blockchains. Front. Comput. Sci. 18, 183104 (2024). https://doi.org/10.1007/s11704-022-2327-7

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