Computer Engineering and Applications ›› 2023, Vol. 59 ›› Issue (16): 16-30.DOI: 10.3778/j.issn.1002-8331.2211-0457

• Research Hotspots and Reviews • Previous Articles     Next Articles

Review of Key Technologies for Blockchain System Performance Optimization

SONG Chuangang, LI Leixiao, GAO Haoyu   

  1. 1.School of Data Science and Application, Inner Mongolia University of Technology, Hohhot 010080, China
    2.School of Cyberspace Security(School of Cryptography), Hainan University, Haikou 570228, China
  • Online:2023-08-15 Published:2023-08-15

区块链系统性能优化关键方法综述

宋传罡,李雷孝,高昊昱   

  1. 1.内蒙古工业大学 数据科学与应用学院,呼和浩特 010080
    2.海南大学 网络空间安全学院(密码学院),海口 570228

Abstract: Blockchain is a distributed system built by combining distributed architecture, cryptography and incentive mechanism, which has the characteristics of immutability, decentralization and unforgeability, and can realize secure peer-to-peer transactions in an untrusted environment, so attracting widespread attention. However, blockchain technology has the problem of low system efficiency and cannot be applied on a large scale. Starting from the data structure and development trend of blockchain, the current performance problems are analyzed. The existing problems are summarized and discussed from two aspects of on-chain expansion and off-chain expansion. The latest research progress of the current blockchain expansion scheme technology is comprehensively expounded from the mainstream aspects such as sharding and directed acyclic graphs, and the optimization method combined with the deep reinforcement learning method is added to the on-chain expansion part. Finally, the future blockchain optimization direction is proposed.

Key words: blockchain, performance improvement, deep reinforcement learning, decentralization

摘要: 区块链是结合分布式架构、密码学以及激励机制等方法构建的一个分布式系统,具有不可篡改性、去中心化和不可伪造性等特点,在不受信任的环境下可以实现安全的点对点交易,受到广泛关注。但是区块链技术存在着系统效能较低的问题,无法被大规模落地应用。从区块链的数据结构和发展趋势出发,对目前区块链存在的性能问题进行了分析。针对存在的问题,从链上扩容、链下扩容两方面进行归纳讨论。针对分片、有向无环图等主流方法,全面总结分析了目前区块链扩容技术的最新研究进展,并且在链上扩容部分加入了与深度强化学习相结合的优化方法。最后对未来的区块链优化方向提出了展望。

关键词: 区块链, 性能提升, 深度强化学习, 去中心化