An Efficient Blockchain Transaction Retrieval System

Hangwei Feng, Jinlin Wang and Yang Li ()
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Hangwei Feng: National Network New Media Engineering Research Center, Institute of Acoustics, Chinese Academy of Sciences, No. 21, North Fourth Ring Road, Haidian District, Beijing 100190, China
Jinlin Wang: National Network New Media Engineering Research Center, Institute of Acoustics, Chinese Academy of Sciences, No. 21, North Fourth Ring Road, Haidian District, Beijing 100190, China
Yang Li: National Network New Media Engineering Research Center, Institute of Acoustics, Chinese Academy of Sciences, No. 21, North Fourth Ring Road, Haidian District, Beijing 100190, China

Future Internet, 2022, vol. 14, issue 9, 1-21

Abstract: In the era of the digital economy, blockchain has developed well in various fields, such as finance and digital copyright, due to its unique decentralization and traceability characteristics. However, blockchain gradually exposes the storage problem, and the current blockchain stores the block data in third-party storage systems to reduce the node storage pressure. The new blockchain storage method brings the blockchain transaction retrieval problem. The problem is that when unable to locate the block containing this transaction, the user must fetch the entire blockchain ledger data from the third-party storage system, resulting in huge communication overhead. For this problem, we exploit the semi-structured data in the blockchain and extract the universal blockchain transaction characteristics, such as account address and time. Then we establish a blockchain transaction retrieval system. Responding to the lacking efficient retrieval data structure, we propose a scalable secondary search data structure BB+ tree for account address and introduce the I2B+ tree for time. Finally, we analyze the proposed scheme’s performance through experiments. The experiment results prove that our system is superior to the existing methods in single-feature retrieval, concurrent retrieval, and multi-feature hybrid retrieval. The retrieval time under single feature retrieval is reduced by 40.54%, and the retrieval time is decreased by 43.16% under the multi-feature hybrid retrieval. It has better stability in different block sizes and concurrent retrieval scales.

Keywords: blockchain retrieval; B+ tree; BB+ tree; I2B+ tree (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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