电信科学 ›› 2020, Vol. 36 ›› Issue (2): 1-12.doi: 10.11959/j.issn.1000-0801.2020037
所属专题: 区块链
• 综述 • 下一篇
修回日期:
2020-02-07
出版日期:
2020-02-20
发布日期:
2020-05-19
作者简介:
宋琪杰(1994- ),男,浙江工业大学计算机科学与技术学院硕士生,主要研究方向为区块链和物联网安全|陈铁明(1978- ),男,博士,浙江工业大学计算机科学与技术学院教授,主要研究方向为网络空间安全与大数据智能分析|陈园(1994- ),女,浙江工业大学计算机科学与技术学院硕士生,主要研究方向为物联网安全|马栋捷(1994- ),男,浙江工业大学计算机科学与技术学院硕士生,主要研究方向为信息安全|翁正秋(1981- ),女,浙江工业大学计算机科学与技术学院博士生,温州职业技术学院大数据技术与应用专业负责人、副教授,主要研究方向为数据安全与大数据技术
基金资助:
Qijie SONG1,Tieming CHEN1,2(),Yuan CHEN1,Dongjie MA1,Zhengqiu WENG1,3
Revised:
2020-02-07
Online:
2020-02-20
Published:
2020-05-19
Supported by:
摘要:
区块链的本质是一个去中心化的分布式账本系统;物联网是由海量异构终端接入互联而成,具备天然的分布式特征,因此两者结合的物联网区块链被广泛看好。同时,由于物联网感知终端的异构性、计算存储及数据传输能力都受限等特性,使物联网区块链面临较大挑战,其中密码共识技术成为关键问题。在总结当前区块链共识算法的基础上,分析其对物联网区块链的适用性,介绍了几大物联网区块链平台及共识机制应用现状,并阐述了针对物联网区块链的共识机制优化研究进展。最后展望物联网区块链的优化技术,总结有潜力的研究方向。
中图分类号:
宋琪杰,陈铁明,陈园,马栋捷,翁正秋. 面向物联网区块链的共识机制优化研究[J]. 电信科学, 2020, 36(2): 1-12.
Qijie SONG,Tieming CHEN,Yuan CHEN,Dongjie MA,Zhengqiu WENG. Research on consensus mechanism optimization for IoT blockchain[J]. Telecommunications Science, 2020, 36(2): 1-12.
表1
区块链共识算法对比[17]"
分类 | 共识算法 | 提出时间 | 计算消耗 | 容忍恶意节点数 | 去中心化程度 | 可监管性 | 应用 |
PoW[ | 1999年 | 大 | <1/2 | 完全 | 弱 | 比特币,Permacoin | |
PoS[ | 2011年 | 中等 | <1/2 | 完全 | 弱 | Peercoin | |
DPoS[ | 2013年 | 低 | <1/2 | 完全 | 弱 | EOS | |
Ouroboros[ | 2017年 | 低 | <1/2 | 半中心化 | 强 | Cardno | |
PoA[ | 2014年 | 大 | <1/2 | 半中心化 | 强 | 以太坊私链,Oracles Network | |
PoB[ | 2014年 | 大 | <1/2 | 半中心化 | 强 | Slimcoin | |
证明类共识 | PoC[ | 2016年 | 大 | — | 完全 | 弱 | 文件共享 |
PoD(Proof of Devotion) | — | 中等 | — | 半中心化 | 强 | 星云链 | |
PoE[ | 2016年 | 未知 | — | 完全 | 弱 | HeroNode、DragonChain | |
PoI[ | 2015年 | 低 | — | 完全 | 弱 | NEM | |
PoR[ | 2014年 | 低 | <1/4 | 完全 | 弱 | 文件共享 | |
PoET[ | 2017年 | 小 | <1/2 | 半中心化 | 强 | 锯齿湖(sawtooth lake) | |
PoP[ | 2012年 | 大 | <1/4 | 完全 | 弱 | Bitcoin | |
拜占庭共识 | PBFT[ | 1999年 | 低 | <1/3 | 半中心化 | 强 | 超级账本 |
Raft | 2013年 | — | 半中心化 | 强 | etcd | ||
有向无环图 | DAG[ | — | 低 | — | 完全 | 弱 | IoTA |
表3
物联网区块链共识机制优化研究现状与特点"
应用方向 | 相关工作 | 概述 | 性能优势 |
共识算法改进 | 基于信任的PoW算法改进[ | 对节点的可信任性进行评估,通过系数调节每个节点的挖矿难度 | 增加恶意节点的算力消耗,使之得不到记账权,同时在选择时降低选中恶意节点的概率,增加容错性 |
基于PBFT的容错优化[ | 使用离群检测算法,通过数据进行恶意节点划分 | 将共识算法分层,第一层使用恶意节点检测并分辨出恶意节点,第二层进行PBFT共识。增强容错性 | |
DRL助力共识机制[ | 使用深度强化学习进行块生成等调整 | 将DRL技术运用于块的生成、调整,动态调节系统达到平衡、高效 | |
DAG主链子链结合[ | 基于 DAG 的主链子链形式区分领域和区块 | DAG 的主子链形式有效增加了区块链的吞吐量,同时减小了区块数据的存储 | |
数据层优化 | 基于数据压缩的区块链系统[ | 将区块链中的数据区块进行压缩,降低存储空间,缓解设备存储压力 | 大大增强设备的存储能力,降低因设备存储空间过小造成的性能问题 |
基于FPGA存储模块的高性能数据读写架构[ | 制作外部存储模块,通信过程中请求高性能存储模块而非服务器 | 高性能的存储模块有效提高了数据的读写,降低数据在传输过程中的性能消耗,提高共识效率 | |
通过边缘计算对数据进行整理优化[ | 通过边缘计算和分布式结合的方式验证数据质量 | 在区块链架构中提出边缘计算层,改善数据质量和错误数据检测,增强共识容错率 | |
架构服务优化 | 物联网+区块链架构与服务[ | 将区块链中的不同层与物联网中不同层进行结合,构建新架构 | 架构的整合规避了物联网存在的缺点,将两者结合形成稳定的新结构,使区块链应用于物联网上 |
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