增强区块链可扩展性的自适应梅克尔树

IF 6 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Oleksandr Kuznetsov , Dzianis Kanonik , Alex Rusnak , Anton Yezhov , Oleksandr Domin , Kateryna Kuznetsova
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引用次数: 0

摘要

区块链技术的可扩展性仍然是一个关键挑战,阻碍了其在各行各业的广泛应用。区块链架构的基本组成部分梅克尔树负责确保数据完整性和促进高效验证流程,本研究通过提出梅克尔树的自适应重组,引入了一种创新方法来应对这一挑战。与传统的静态树结构不同,我们的自适应模型可根据使用模式动态调整这些树的配置,从而显著减少验证所需的平均路径长度,进而减少与这些流程相关的计算开销。通过一个全面的概念框架,我们描述了自适应重组的方法,包括二进制和非二进制树配置。我们通过一系列详细的示例验证了这一框架,证明了我们的方法切实可行并提高了效率。为了对我们提出的方法的有效性进行实证评估,我们使用来自以太坊区块链的真实数据进行了严格的实验。实验结果令人信服地证明了自适应梅克尔树的优越性,在树重组的初始阶段观察到的效率收益高达 30% 甚至更高。此外,我们还与现有的可扩展性解决方案进行了比较分析,突出了自适应重组在简单性、安全性和效率提升方面的独特优势,而且不会引入额外的复杂性或依赖性。这项研究的意义超出了理论上的进步,它为区块链数据验证提供了一种可扩展、安全、高效的方法,可促进区块链技术在金融、供应链管理等领域的广泛应用。随着区块链生态系统的不断发展,本文概述的原则、方法和实证研究结果将为其发展和成熟做出重大贡献。声明 本文的研究成果已在 ETHDenver 2024(https://www.ethdenver.com/)上发表,这是一个领先的创新节,旨在倡导 Web3 社区在塑造区块链技术未来中的作用。我们的演讲视频见 https://www.youtube.com/watch?v=-jjYVCAQkNE。本文原稿可在预印本存档网站 https://arxiv.org/abs/2403.00406 上查阅。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Adaptive Merkle trees for enhanced blockchain scalability

Adaptive Merkle trees for enhanced blockchain scalability

The scalability of blockchain technology remains a critical challenge, hindering its widespread adoption across various sectors. This study introduces an innovative approach to address this challenge by proposing the adaptive restructuring of Merkle trees, fundamental components of blockchain architecture responsible for ensuring data integrity and facilitating efficient verification processes. Unlike traditional static tree structures, our adaptive model dynamically adjusts the configuration of these trees based on usage patterns, significantly reducing the average path length required for verification and, consequently, the computational overhead associated with these processes. Through a comprehensive conceptual framework, we delineate the methodology for adaptive restructuring, encompassing both binary and non-binary tree configurations. This framework is validated through a series of detailed examples, demonstrating the practical feasibility and the efficiency gains achievable with our approach. To empirically assess the effectiveness of our proposed method, we conducted rigorous experiments using real-world data from the Ethereum blockchain. The results provide compelling evidence for the superiority of adaptive Merkle trees, with efficiency gains of up to 30% and higher observed during the initial stages of tree restructuring. Moreover, we present a comparative analysis with existing scalability solutions, highlighting the unique advantages of adaptive restructuring in terms of simplicity, security, and efficiency enhancement without introducing additional complexities or dependencies. This study’s implications extend beyond theoretical advancements, offering a scalable, secure, and efficient method for blockchain data verification that could facilitate broader adoption of blockchain technology in finance, supply chain management, and beyond. As the blockchain ecosystem continues to evolve, the principles, methodologies, and empirical findings outlined herein are poised to contribute significantly to its growth and maturity. Statement The findings of this article were presented at ETHDenver 2024 (https://www.ethdenver.com/), a leading innovation festival that champions the Web3 community’s role in shaping the future of blockchain technology. A video of our presentation can be found at https://www.youtube.com/watch?v=-jjYVCAQkNE. The original manuscript of this article is available on the preprint archive at https://arxiv.org/abs/2403.00406.

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来源期刊
Internet of Things
Internet of Things Multiple-
CiteScore
3.60
自引率
5.10%
发文量
115
审稿时长
37 days
期刊介绍: Internet of Things; Engineering Cyber Physical Human Systems is a comprehensive journal encouraging cross collaboration between researchers, engineers and practitioners in the field of IoT & Cyber Physical Human Systems. The journal offers a unique platform to exchange scientific information on the entire breadth of technology, science, and societal applications of the IoT. The journal will place a high priority on timely publication, and provide a home for high quality. Furthermore, IOT is interested in publishing topical Special Issues on any aspect of IOT.
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