通过模块化视角探索区块链技术:一项调查

IF 23.8 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS ACM Computing Surveys Pub Date : 2024-04-11 DOI:10.1145/3657288
Minghui Xu, Yihao Guo, Chunchi Liu, Qin Hu, Dongxiao Yu, Zehui Xiong, Dusit Niyato, Xiuzhen Cheng
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引用次数: 0

摘要

近年来,区块链因其提供可信性而可能给各行各业带来革命性的变化,因而备受关注。为了全面研究区块链系统,本文从宏观层面概述了最流行的区块链系统,并从微观层面分析了一般区块链框架及其关键组件。宏观层面的探讨为区块链专业人士多年来为提高区块链性能所做的努力提供了一个大视野,而微观层面的调查则详细介绍了区块链构建模块,以便深入理解技术。更具体地说,本文介绍了一个通用的模块化区块链分析框架,该框架将区块链系统分解为相互作用的模块,然后对主要模块进行研究,在微观层面涵盖了网络、共识和分布式账本等区块链的基本组成部分。该框架和模块分析共同为设计可扩展、灵活、应用自适应的区块链奠定了基础,可满足各种需求。此外,本文还探讨了可与区块链集成以扩展功能的流行技术,并强调了主要挑战。这样的研究为克服设计新型区块链系统的障碍提供了重要见解,并促进了区块链作为数字基础设施服务于新应用的进一步发展。
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Exploring Blockchain Technology through a Modular Lens: A Survey

Blockchain has attracted significant attention in recent years due to its potential to revolutionize various industries by providing trustlessness. To comprehensively examine blockchain systems, this article presents both a macro-level overview on the most popular blockchain systems, and a micro-level analysis on a general blockchain framework and its crucial components. The macro-level exploration provides a big picture on the endeavors made by blockchain professionals over the years to enhance the blockchain performance while the micro-level investigation details the blockchain building blocks for deep technology comprehension. More specifically, this article introduces a general modular blockchain analytic framework that decomposes a blockchain system into interacting modules and then examines the major modules to cover the essential blockchain components of network, consensus, and distributed ledger at the micro-level. The framework as well as the modular analysis jointly build a foundation for designing scalable, flexible, and application-adaptive blockchains that can meet diverse requirements. Additionally, this article explores popular technologies that can be integrated with blockchain to expand functionality and highlights major challenges. Such a study provides critical insights to overcome the obstacles in designing novel blockchain systems and facilitates the further development of blockchain as a digital infrastructure to service new applications.

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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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