一个用于车辆互联网的区块链解决方案,具有更好的过和适应能力
1School of Artificial Intelligence, Liaoning University of Engineering and Technology, No. 188 Longwan Street, Sijiatun Street, Xingcheng 125100, China.
Sensors (Basel, Switzerland)
|February 26, 2025
概括
本研究介绍了AE-PBFT,这是用于车辆互联网 (IoV) 的自适应共识算法. 它通过动态调整共识组和节点信任来提高效率和可靠性,以获得更好的实时性能.
科学领域:
- 计算机科学 计算机科学
- 网络工程 网络工程
- 分布式系统 分布式系统
背景情况:
- 传统的汽车互联网 (IoV) 共识算法存在高延迟,低可靠性和差故障耐受性问题.
- 这些局限性阻碍了实时调整,并使 IoV 系统易受低效率和环境挑战的影响.
研究的目的:
- 为 IoV 系统提出一种新的,自适应的共识算法.
- 解决现有的共识机制在延迟,可靠性和容错性方面的局限性.
主要方法:
- 引入了一个信任管理模型,记录历史节点行为以逐渐加速.
- 实施了基于环境适应性变化的动态共识组划分机制.
- 开发了AE-PBFT (基于自适应环境的实用拜占庭式故障容忍) 算法.
主要成果:
- 通过高效的节点选,AE-PBFT算法证明了减少共识延迟.
- 通过对共识组大小的自适应性调整,提高了系统可靠性和容错性.
- 实验结果显示,与IOV环境中的现有解决方案相比,性能优越.
结论:
- 拟议的AE-PBFT算法在IoV系统的共识延迟,可靠性和容错性方面提供了显著的改进.
- AE-PBFT非常适合车辆互联网的动态和苛刻的操作条件.
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