GHOSTForge: A Scalable Consensus Mechanism for DAG-Based Blockchains

Misbah Khan;Shabnam Kasra Kermanshahi;Jiankun Hu
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引用次数: 0

Abstract

Blockchain scalability has long been a critical issue, and Directed Acyclic Graphs (DAGs) offer a promising solution by enabling higher throughput. However, despite their scalability, achieving global convergence or consensus in heterogeneous DAG networks remains a significant challenge. This work, introduces GHOSTForge, building on the Greedy Heaviest-Observed Sub-tree (GHOST) protocol to address these challenges. GHOSTForge incorporates unique coloring and scoring mechanisms alongside stability thresholds and order-locking processes. This protocol addresses the inefficiencies found in existing systems, such as PHANTOM, by offering a more proficient two-level coloring and scoring method that eliminates circular dependencies and enhances scalability. The use of stability thresholds enables the early locking of block orders, reducing computational overhead while maintaining robust security. GHOSTForge's design adapts dynamically to varying network conditions, ensuring quick block order convergence and strong resistance to attacks, such as double-spending. Our experimental results demonstrate that GHOSTForge excels in achieving both computational efficiency and rapid consensus, positioning it as a powerful and scalable solution for decentralized, heterogeneous DAG networks.
GHOSTForge:基于 DAG 的区块链可扩展共识机制
长期以来,区块链的可扩展性一直是一个关键问题,而有向无环图(DAG)通过实现更高的吞吐量提供了一种前景广阔的解决方案。然而,尽管 DAG 具有可扩展性,但在异构 DAG 网络中实现全局收敛或共识仍是一项重大挑战。本研究在贪婪最重观测子树(GHOST)协议的基础上引入了 GHOSTForge,以应对这些挑战。GHOSTForge 结合了独特的着色和评分机制,以及稳定性阈值和顺序锁定过程。该协议解决了 PHANTOM 等现有系统的低效问题,提供了更完善的两级着色和评分方法,消除了循环依赖关系,增强了可扩展性。稳定性阈值的使用实现了对区块顺序的早期锁定,减少了计算开销,同时保持了稳健的安全性。GHOSTForge 的设计能动态适应不同的网络条件,确保区块顺序快速收敛,并能有效抵御双重花费等攻击。我们的实验结果表明,GHOSTForge 在实现计算效率和快速共识方面表现出色,是去中心化、异构 DAG 网络的强大、可扩展的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
12.60
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