结合社区发现和局部恢复码的区块链扩容研究

doi:10.3778/j.issn.1002-8331.2109-0493

摘要/Abstract

摘要： 区块链全节点需要存储完整的账本，不能满足数据快速增长的需求，其存储扩容成为当前研究热点之一。现有最优研究成果虽然结合分片和RS（Reed-Solomon）纠删码技术，降低了存储开销，实现了数据可恢复，但存在网络开销较高和跨节点数据请求效率较低的问题。因此，提出了一种基于社区发现和局部恢复码（local reconstruction codes，LRC）的区块链存储扩容方案，一定程度上解决了这些问题。改进现有基于传导性的社区发现方法，在此基础上提出了一种区块链节点分组方法，使平均连接速度更快的节点分为一组，有效地缩短了跨节点请求区块的响应时间；采用了更优的LRC码来替代RS纠删码，利用更少的原始数据实现单点故障数据恢复，降低了网络开销。大量实验结果表明提出的存储方案在保持目前最优方案的数据恢复能力和存储开销的基础上，能有效减少网络开销和跨节点请求区块的时间。

关键词: 区块链, 存储扩容, 社区发现, 局部恢复码

Abstract: The full node in blockchain needs to store a complete ledger, which can’t adapt to the rapid growth of data. Blockchain storage expansion has become one of the current research hotspots. Although the best research results combine sharding and Reed-Solomon（RS） erasure code technics can reduce storage overhead and realize data recovery, there are some problems such as high network overhead and low efficiency of requesting data across node. Therefore, a blockchain storage expansion scheme based on community detection and local reconstruction codes（LRC） is proposed to solve these problems. First, by improving the existing community detection algorithm based on conductance, it proposes a blockchain nodes grouping method, for which can form groups containing nodes with faster network speed in average, the response time of requesting block across node is effectively shortened. Then LRC is selected to replace RS code, which can recovery data with less original data when meeting single point of failure and reduce network overhead. Experimental results show the proposed scheme can effectively reduce the network overhead and the time of requesting block across node while maintaining the data recovery ability and storage overhead of the current optimal solution.

Key words: blockchain, storage expansion, community detection, local reconstruction codes

姜承扬, 庞俊, 贾大宇, 于明鹤, 信俊昌, 刘晨. 结合社区发现和局部恢复码的区块链扩容研究[J]. 计算机工程与应用, 2023, 59(5): 297-304.

JIANG Chengyang, PANG Jun, JIA Dayu, YU Minghe, XIN Junchang, LIU Chen. Research on Blockchain Expansion Combining Community Detection and Local Reconstruction Code[J]. Computer Engineering and Applications, 2023, 59(5): 297-304.

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