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Aggregation-chain: a consortium blockchain based multi-chain data sharing framework with efficient query

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Abstract

In recent years, blockchain technology has emerged as a topic of increasing interest within the field of computer science research. Due to its characteristics of decentralisation, information traceability, and tamper-resistance, it has been widely applied in data sharing research. Nevertheless, a number of outstanding issues remain to be resolved. Firstly, in the current stage of research on blockchain-based data sharing, there is a tendency to focus on the case of a single chain, with relatively little consideration given to multi-chain (i.e., multiple blockchains or multiple blockchain-based data sharing systems) together for data sharing. This can lead to the problem of data silos. Secondly, some studies utilise public chains as the underlying framework for data sharing frameworks or systems. However, the mining mechanism of public chains can result in a significant waste of resources. Furthermore, query optimisation on blockchain is a significant area of research in the field of blockchain. In light of the aforementioned issues, we proposed a multi-chain data sharing framework based on consortium blockchain, wherein the metadata of data on multiple blockchains can be aggregated and reorganised. In order to enhance the query efficiency of our proposed multi-chain data sharing framework, we have constructed an off-chain query service. Concurrently, in order to guarantee the consistency of the data on the off-chain query service with the blockchain data and to authenticate the data, we have proposed an effective data consistency mechanism by improving the database fingerprint generation algorithm. Furthermore, an asymmetric encryption transmission method is employed to guarantee the security of data transmission. Finally, comparative experiments and various analyses show that our proposed data sharing framework contains various features. It can efficiently aggregate metadata and securely transfer data, significantly improve the efficiency in terms of data querying and database fingerprint generate rate and improve the throughput of database fingerprint generate algorithms.

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Funding

This work was supported by the National Key Research and Development Projects (2022YFC3302500), Guangxuan Scholar Program of Shenyang Ligong University.

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Authors and Affiliations

  1. School of Information Science and Engineering, Shenyang Ligong University, Shenyang, 110159, Liaoning, China

    Leda Qu, Feng Wen & Zhuo Wang

  2. School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang, 110159, Liaoning, China

    Haixin Huang

Authors
  1. Leda Qu
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  2. Feng Wen
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  3. Haixin Huang
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  4. Zhuo Wang
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Contributions

Leda Qu: Conceptualization, Methodology, Software, Data curation, Validation, Writing-Original draft preparation, Visualization, Writing-Editing. Feng Wen: Conceptualization, Methodology, Software, Supervision, Writing-Reviewing. Haixin Huang: Conceptualization, Methodology. Zhuo Wang: Software, Validation, Visualization.

Corresponding author

Correspondence to Feng Wen.

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Qu, L., Wen, F., Huang, H. et al. Aggregation-chain: a consortium blockchain based multi-chain data sharing framework with efficient query. Cluster Comput 28, 46 (2025). https://doi.org/10.1007/s10586-024-04777-w

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