通过基于多功能的联合学习,提高区块链港口互联网跨链传输的效率和安全性
Zeqiang Xie1, Xiaowei Zhang2, Xinbing Liu3
1College of Artificial Intelligence, Dalian Maritime University, Dalian, 116026, China. corresponding.zeqiang@dlmu.edu.cn.
Scientific reports
|February 20, 2025
概括
本研究介绍了在港口地区区块链物联网 (IoT) 系统的负载适应性跨链控制方法. 它提高了传输效率和安全性,在动态环境中优于传统方法.
科学领域:
- 计算机科学 计算机科学
- 网络工程 网络工程
- 网络安全 网络安全
背景情况:
- 区块链物联网 (IoT) 系统需要高效和安全的跨链通信.
- 传统方法忽视了性能优化,特别是在像港口地区这样的高动态环境中.
- 港口地区面临诸如网络拥堵,高延迟和资源利用不均等等挑战.
研究的目的:
- 为港口地区的区块链物联网提出一种新的负载适应性跨链控制方法.
- 为了提高传输效率,可扩展性和稳定性,在动态,高一致性环境中.
- 在跨链通信中,平衡性能优化与数据隐私.
主要方法:
- 集成多功能联合学习和自适应的多通道联合总线控制.
- 实施分布式智能调度机制,以实现分散的任务协调.
- 联合学习的应用用于保护隐私的跨链通信优化.
主要成果:
- 在吞吐量和延迟方面有显著的改进.
- 与传统的集中式方法相比,减少了数据包丢失率.
- 证明了平衡动态网络负载并最大限度地减少干扰的能力.
结论:
- 拟议的方法为区块链物联网系统提供了可扩展和安全的解决方案.
- 它有效地解决了复杂环境中传统跨链方法的局限性.
- 这项工作弥合了跨链优化中的性能和隐私之间的差距.
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