士-双胞胎:超越5G数字双胞胎网络框架的迷你巨人模型驱动,具有语义安全通信和计算
Yang Hong1, Jun Wu2, Rosario Morello3
1Graduate School of Information, Production and System, Waseda University, Fukuoka, 8080135, Japan.
Scientific reports
|August 17, 2024
概括
本研究介绍了LLM-Twin,这是使用大型语言模型 (LLM) 进行数字双胞胎网络 (DTNs) 的新框架. LLM-Twin增强了下一代网络的通信,计算和多式联网数据处理.
科学领域:
- 通信工程 通信工程 通信工程
- 人工智能的人工智能
- 网络系统 网络系统
背景情况:
- 超越5G网络和数字双胞胎网络 (DTNs) 对于弥合物理和数字领域至关重要.
- 当前的DTN在通信/计算效率和处理多式联网数据方面面临着挑战.
- 对于DTNs的现有安全措施通常会引入性能开销.
研究的目的:
- 提出一个由LLM授权的DTN框架,LLM-Twin,解决目前的DTN局限性.
- 在DTN中提高通信,计算和多模式数据处理的效率.
- 为先进的DTN应用程序引入安全高效的框架.
主要方法:
- 开发数字双胞胎语义网络 (DTSN),利用LLM进行高效的数据处理.
- 实施一个小型巨型合作方案,用于在DTNs中部署LLM.
- 为LLM-Twin设计一个本地安全策略,以保持效率.
主要成果:
- LLM-Twin在DTNs中展示了改进的通信和计算效率.
- 该框架有效地处理多式联运数据处理需求.
- 数字实验和案例研究验证了LLM-Twin的可行性和性能.
结论:
- 通过整合LLMs,LLM-Twin代表了DTN技术的重大进步.
- 拟议的DTSN和协作方案为复杂的DTN场景提供了高效的解决方案.
- 这项工作开创了LLM在语义层面对DTNs的应用,提高了他们的能力.
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