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Open Access

On Time-Aware Cross-Blockchain Data Migration

Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518000, China
University of Chinese Academy of Sciences, Beijing 100000, China
Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen 518000, China
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Abstract

With the widespread adoption of blockchain applications, the imperative for seamless data migration among decentralized applications has intensified. This necessity arises from various factors, including the depletion of blockchain disk space, transitions between blockchain systems, and specific requirements such as temporal data analysis. To meet these challenges and ensure the sustained functionality of applications, it is imperative to conduct time-aware cross-blockchain data migration. This process is designed to facilitate the smooth iteration of decentralized applications and the construction of a temporal index for historical data, all while preserving the integrity of the original data. In various application scenarios, this migration task may encompass the transfer of data between multiple blockchains, involving movements from one chain to another, from one chain to several chains, or from multiple chains to a single chain. However, the success of data migration hinges on the careful consideration of factors such as the reliability of the data source, data consistency, and migration efficiency. This paper introduces a time-aware cross-blockchain data migration approach tailored to accommodate diverse application scenarios, including migration between multiple chains. The proposed solution integrates a collective mechanism for controlling, executing, and storing procedures to address the complexities of data migration, incorporating elements such as transaction classification and matching. Extensive experiments have been conducted to validate the efficacy of the proposed approach.

References

[1]
S. Nakamoto, Bitcoin: A peer-to-peer electronic cash system, https://www.klausnordby.com/bitcoin/Bitcoin_Whitepaper_Document_HD.pdf, 2008.
[2]
G. Wood, Ethereum: A secure decentralised generalized transaction ledger, https://cryptodeep.ru/doc/paper.pdf, 2014.
[3]

T. T. Kuo, H. E. Kim, and L. Ohno-Machado, Blockchain distributed ledger technologies for biomedical and health care applications, J. Am. Med. Inform. Assoc., vol. 24, no. 6, pp. 1211–1220, 2017.

[4]

S. Saberi, M. Kouhizadeh, J. Sarkis, and L. Shen, Blockchain technology and its relationships to sustainable supply chain management, Int. J. Prod. Res., vol. 57, no. 7, pp. 2117–2135, 2019.

[5]

P. Treleaven, R. G. Brown, and D. Yang, Blockchain technology in finance, Computer, vol. 50, no. 9, pp. 14–17, 2017.

[6]
B. Nasrulin, M. Muzammal, and Q. Qu, ChainMOB: mobility analytics on blockchain, in Proc. 2018 19th IEEE Int. Conf. Mobile Data Management (MDM), Aalborg, Denmark, 2018, pp. 292&293.
[7]

M. Muzammal, Q. Qu, and B. Nasrulin, Renovating blockchain with distributed databases: An open source system, Future Gener. Comput. Syst., vol. 90, pp. 105–117, 2019.

[8]

J. Xie, F. R. Yu, T. Huang, R. Xie, J. Liu, and Y. Liu, A survey on the scalability of blockchain systems, IEEE Netw. Mag. Glob. Internetworking, vol. 33, no. 5, pp. 166–173, 2019.

[9]

D. Gao, C. S. Jensen, R. T. Snodgrass, and M. D. Soo, Join operations in temporal databases, VLDB J., vol. 14, no. 1, pp. 2–29, 2005.

[10]

M. Mokbel, T. Ghanem, and W. Aref, Spatio-temporal access methods, IEEE Data Eng. Bull., vol. 26, no. 2, pp. 40–49, 2003.

[11]

Y. Kanza, Technical Perspective: Revealing Every Story of Data in Blockchain Systems, ACM SIGMOD Record, vol. 49, no. 1, p. 69, 2020.

[12]
E. Androulaki, A. Barger, V. Bortnikov, C. Cachin, K. Christidis, A. De Caro, D. Enyeart, C. Ferris, G. Laventman, Y. Manevich et al., Hyperledger fabric: a distributed operating system for permissioned blockchains, in Proc. Thirteenth EuroSys Conference, Porto, Portugal, 2018, pp. 1–15.
[13]

S. Das, S. Nishimura, D. Agrawal, and A. El Abbadi, Albatross: Lightweight elasticity in shared storage databases for the cloud using live data migration, Proc. VLDB Endow., vol. 4, no. 8, pp. 494–505, 2011.

[14]
M. Zhang, Q. Qu, L. Ning, J. Fan, and R. Yang, An effective and reliable cross-blockchain data migration approach, in Proc. Parallel and Distributed Computing, Applications and Technologies, Guangzhou, China, 2021. pp. 286–294.
[15]
P. Carreira and H. Galhardas, Efficient development of data migration transformations, in Proc. 2004 ACM SIGMOD Int. Conf. Management of data, Paris, France, 2004, pp. 915–916.
[16]
A. Rüping, Transform! Patterns for data migration, in Transactions on Pattern Languages of Programming III, J. Noble, R. Johnson, U. Zdun, E. Wallingford, eds. Berlin, Heidelberg, Germany: Springer Berlin, Heidelberg, 2013, pp. 1–23.
[17]

S. Biswas, K. Sharif, F. Li, and S. Mohanty, Blockchain for E-health-care systems: Easier said than done, Computer, vol. 53, no. 7, pp. 57–67, 2020.

[18]

M. Herlihy, B. Liskov, and L. Shrira, Cross-chain deals and adversarial commerce, VLDB J., vol. 31, no. 6, pp. 1291–1309, 2022.

[19]
C. T. Ba, A. Michienzi, B. Guidi, M. Zignani, L. Ricci, and S. Gaito, Fork-based user migration in Blockchain Online Social Media, in Proc. 14th ACM Web Science Conference 2022, Barcelona, Spain, 2022, pp. 174–184.
[20]
VeChain, VeChainThor wallet manual including token swap and X node migration, https://cdn.vechain.com/vechainthor wallet manual env1.0.pdf, 2018.
[21]
Z. Gao, H. Li, K. Xiao, and Q. Wang, Cross-chain oracle based data migration mechanism in heterogeneous blockchains, in Proc. 2020 IEEE 40th Int. Conf. Distributed Computing Systems (ICDCS), Singapore, Singapore, 2020, pp. 1263–1268.
[22]
H. D. Bandara, X. Xu, and I. Weber, Patterns for blockchain data migration, in Proc. European Conf. Pattern Languages of Programs 2020, Virtual Event, Germany, 2020, pp. 1–19.
[23]
H. Gupta, S. Hans, K. Aggarwal, S. Mehta, B. Chatterjee, and P. Jayachandran, Efficiently processing temporal queries on hyperledger fabric, in Proc. 2018 IEEE 34th Int. Conf. Data Engineering (ICDE), Paris, France, 2018, pp. 1489–1494.
[24]
H. Gupta, S. Hans, S. Mehta, and P. Jayachandran, On building efficient temporal indexes on hyperledger fabric, in Proc. 2018 IEEE 11th Int. Conf. Cloud Computing (CLOUD), San Francisco, CA, USA, 2018, pp. 294–301.
Tsinghua Science and Technology
Pages 1810-1820
Cite this article:
Zhang M, Qu Q, Ning L, et al. On Time-Aware Cross-Blockchain Data Migration. Tsinghua Science and Technology, 2024, 29(6): 1810-1820. https://doi.org/10.26599/TST.2023.9010136

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Received: 04 August 2022
Revised: 19 March 2023
Accepted: 03 November 2023
Published: 20 June 2024
© The Author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

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