通过为随机区块分配权重改进区块链一致性约束

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Xueping Gong, Qing Zhang, Huizhong Li, Jiheng Zhang
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引用次数: 0

摘要

Ironclad 方法提高区块链一致性并加快区块生产研究人员开发了一种名为 Ironclad 的新方法,以解决基于中本共识协议的区块链的可扩展性限制问题。虽然这些区块链在各种应用中都显示出了前景,但协议的共识特性却带来了固有的可扩展性限制。其中一个关键属性,即一致性,在区块生产速度和系统抵御恶意攻击的安全性之间提出了权衡,从而带来了挑战。为了克服这一问题,研究人员提出了 Ironclad 方法,通过为随机选择的区块分配不同的权重,引入了一种独特的方法。通过将 Ironclad 方法应用于原始中本协议,并对其共识属性进行严格分析,研究人员证明一致性约束有了显著改善。与原始协议相比,这一进步使得区块生成速度大大加快,同时保持了相同的安全保证水平。Ironclad 方法克服了中本共识协议的局限性,为提高区块链的可扩展性提供了一个前景广阔的解决方案。这一突破有可能为区块链应用带来新的可能性,为各行各业提高交易速度和效率铺平道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving Blockchain Consistency Bound by Assigning Weights to Random Blocks
Ironclad Method Boosts Blockchain Consistency and Speeds up Block Production Researchers have developed a novel method called Ironclad to address the scalability limitations of blockchains based on the Nakamoto consensus protocol. Although these blockchains have shown promise in various applications, the consensus properties of the protocol impose inherent scalability constraints. A key property, known as consistency, poses a challenge by presenting a trade-off between block production speed and the system’s security against adversarial attacks. To overcome this, the researchers propose the Ironclad method, which introduces a unique approach by assigning different weights to randomly selected blocks. By applying the Ironclad method to the original Nakamoto protocol and conducting rigorous analysis of its consensus properties, the researchers demonstrate a significant improvement in the consistency bound. This advancement allows for a much faster block production rate compared with the original protocol while maintaining the same level of security guarantees. The Ironclad method presents a promising solution to enhance blockchain scalability, overcoming the limitations of the Nakamoto consensus protocol. This breakthrough has the potential to unlock new possibilities for blockchain applications, paving the way for improved transaction speeds and increased efficiency in various industries.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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