X-RAFT:改进RAFT共识,使区块链更安全的edge - ai - human - iot数据

IF 5.1 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Fengqi Li;Jiaheng Wang;Weilin Xie;Ning Tong;Deguang Wang
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引用次数: 0

摘要

物联网设备的激增、边缘计算的进步以及人工智能技术的创新为边缘人工智能的诞生和发展创造了理想的环境。随着万物互联(IoE)的发展趋势,EdgeAI- Human-IoT架构框架强调了高效数据交换互联的必要性。确保安全的数据共享和高效的数据存储是实现数据无缝互联的关键挑战。通常用于分布式存储的RAFT共识算法由于其简单、易于部署和达成共识的能力,随着物联网规模的扩大而面临限制。节点的计算、通信和存储能力受到限制,数据的安全性仍然是一个问题。为了解决这些复杂的挑战,我们引入了为区块链技术量身定制的X-RAFT共识算法。该算法提高了系统的性能和鲁棒性,减轻了系统负载的影响,增强了系统的可持续性,增加了拜占庭容错性。通过分析和仿真,证明了该方案具有可靠的安全性和高效的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
X-RAFT: Improve RAFT Consensus to Make Blockchain Better Secure EdgeAI-Human-IoT Data
The proliferation of IoT devices, advancements in edge computing, and innovations in AI technology have created an ideal environment for the birth and growth of Edge AI. With the trend towards the Internet of Everything (IoE), the EdgeAI- Human-IoT architectural framework highlights the necessity for efficient data exchange interconnectivity. Ensuring secure data sharing and efficient data storage are pivotal challenges in achieving seamless data interconnection. Owing to its simplicity, ease of deployment, and consensus-reaching capabilities, the RAFT consensus algorithm, which is commonly used in distributed storage, faces limitations as the IoT scale expands. The computational, communication, and storage capabilities of nodes are constraints, and the security of data remains a concern. To address these complex challenges, we introduce the X-RAFT consensus algorithm, which is tailored for blockchain technology. This algorithm enhances system performance and robustness, mitigates the impact of system load, enhances system sustainability, and increases Byzantine fault tolerance. Through analysis and simulations, our proposed solution has been evidenced to provide reliable security and efficient performance.
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来源期刊
IEEE Transactions on Emerging Topics in Computing
IEEE Transactions on Emerging Topics in Computing Computer Science-Computer Science (miscellaneous)
CiteScore
12.10
自引率
5.10%
发文量
113
期刊介绍: IEEE Transactions on Emerging Topics in Computing publishes papers on emerging aspects of computer science, computing technology, and computing applications not currently covered by other IEEE Computer Society Transactions. Some examples of emerging topics in computing include: IT for Green, Synthetic and organic computing structures and systems, Advanced analytics, Social/occupational computing, Location-based/client computer systems, Morphic computer design, Electronic game systems, & Health-care IT.
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