用于去中心化金融协议优化的区块链可提取价值实时发现和挖掘系统

IF 4.5 2区 计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS IEEE Transactions on Computational Social Systems Pub Date : 2024-03-07 DOI:10.1109/TCSS.2024.3386716
Fangzhou Tang;Yuhang Liu;Qian Zhao;Yayun Cheng
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引用次数: 0

摘要

区块链技术的采用催化了去中心化金融(DeFi)的扩张,导致了区块链平台的利用。然而,受共识机制的影响,区块链的去中心化催生了区块链可提取价值(BEV)活动。本研究以区块链可提取价值(BEV)为中心,揭示了一个专为基于套利的区块链可提取价值(DeFi)活动定制的实时发现和挖掘系统(RDMS)。该系统采用创新方法进行本地化计算和执行。它为套利和清算活动建立了一个全面的监控系统,为 DeFi 生态系统做出了积极贡献。利用全天候链上数据索引和事件驱动解析方法,RDMS 可对 BEV 活动进行自动和定期分析。该系统为 BEV 研究提供了宝贵的见解,尤其是在套利和清算活动方面。利用实时监控区块链并应用气体成本降低机制的 RDMS,我们能够利用区块链上的套利策略持续提取价值。实验测试和对比分析验证了 RDMS 的有效性,展示了最小延迟和卓越的气体优化能力。
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Real-Time Discovery and Mining System of Blockchain Extractable Value for Decentralized Finance Protocol Optimization
The adoption of blockchain technology has catalyzed the expansion of decentralized finance (DeFi), leading to the harnessing of blockchain platforms. However, the decentralization of blockchain has given rise to blockchain extractable value (BEV) activities, influenced by consensus mechanisms. This study centers on BEV, unveiling a real-time discovery and mining system (RDMS) tailored for arbitrage-based DeFi activities. The system employs innovative methodologies for localized computation and execution. It establishes a comprehensive monitoring system for arbitrage and liquidation activities, contributing positively to the DeFi ecosystem. Leveraging round-the-clock on-chain data indexing and event-driven parsing methods, the RDMS enables automated and periodic analysis of BEV activities. This system provides valuable insights for BEV research, particularly in the context of arbitrage and liquidation activities. And we are able to consistently extract value using arbitrage strategies on blockchains, using RDMS that monitors the chain in real time and applies gas cost reduction mechanisms. Experimental testing and comparative analysis validate the RDMS's effectiveness, showcasing minimal latency and remarkable gas optimization capabilities.
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来源期刊
IEEE Transactions on Computational Social Systems
IEEE Transactions on Computational Social Systems Social Sciences-Social Sciences (miscellaneous)
CiteScore
10.00
自引率
20.00%
发文量
316
期刊介绍: IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.
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Table of Contents Guest Editorial: Special Issue on Dark Side of the Socio-Cyber World: Media Manipulation, Fake News, and Misinformation IEEE Transactions on Computational Social Systems Publication Information IEEE Transactions on Computational Social Systems Information for Authors IEEE Systems, Man, and Cybernetics Society Information
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