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An Efficient Data Reduction Method for DAG Blockchain

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Proceedings of the 13th International Conference on Computer Engineering and Networks (CENet 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1127))

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Abstract

Compared with the traditional blockchain, the blockchain system based on directed acyclic graph (DAG) has higher throughput and greater storage pressure, and there is also redundancy of transaction data in the block, which is caused by concurrent block sending, that is, the same transaction may appear in different blocks, and different blocks are attached to the DAG at the same time, which aggravates the storage pressure. In this paper, to solve the above problems, we propose a method that can reduce data twice. The first data reduction is aimed at the redundancy in the block, which is in the blockchain system based on DAG. And the second data reduction is based on the user's experience and the first basis. The experimental results show that the proposed method can save 92.18% of the storage space and effectively alleviate the storage pressure.

Supported by the Guangxi NSF Project under Grant 2022GXNSFBA035645; by the Guangxi Key Research and Development Program under Grant AB20238026; by the Chinese NSF Project under Grant 6217070229; by the Director Fund of Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education (Guilin University of Electronic Technology) under Grant CRKL210104; and by the Innovation Project of GUET Graduate Education under Grant 2022YCXS052.

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Correspondence to Dongyan Huang .

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Zhang, C., Huang, D. (2024). An Efficient Data Reduction Method for DAG Blockchain. In: Zhang, Y., Qi, L., Liu, Q., Yin, G., Liu, X. (eds) Proceedings of the 13th International Conference on Computer Engineering and Networks. CENet 2023. Lecture Notes in Electrical Engineering, vol 1127. Springer, Singapore. https://doi.org/10.1007/978-981-99-9247-8_35

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  • DOI: https://doi.org/10.1007/978-981-99-9247-8_35

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-9246-1

  • Online ISBN: 978-981-99-9247-8

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