数据与模型协同驱动的智能光网络架构与关键技术

谷志群; 张佳玮; 纪越峰; 于浩; 塔里克·塔勒布

doi:10.11959/j.issn.1000-0801.2022163

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数据与模型协同驱动的智能光网络架构与关键技术

专题：未来光通信技术 | 更新时间：2024-06-05

- 数据与模型协同驱动的智能光网络架构与关键技术
- Network architecture and key technologies of intelligent optical networks driven by data and model
- 电信科学 2022年38卷第7期页码：18-30
- 作者机构：
  
  1. 北京邮电大学信息光子学与光通信国家重点实验室，北京 100876
  2. 奥卢大学，芬兰奥卢 90570
- 作者简介：
  
  [ "谷志群（1986- ），女，博士，北京邮电大学信息与通信工程学院讲师，主要研究方向为智能光网络" ]
  [ "张佳玮（1984- ），男，博士，北京邮电大学信息与通信工程学院副教授、硕士生导师，主要研究方向为光与无线融合网络" ]
  [ "纪越峰（1960- ），男，博士，北京邮电大学信息与通信工程学院教授、博士生导师，主要研究方向为光通信网络理论与技术" ]
  [ "于浩（1992- ），男，奥卢大学无线通信中心在站博士后，主要研究方向为确定性网络、边缘智能网络等" ]
  [ "塔里克·塔勒布（1977- ），男，奥卢大学无线通信中心教授，主要研究方向为网络虚拟化、软件定义网络等" ]
- 基金信息：
  
  国家重点研发计划项目;The National Key Research and Development Program of China(2018YFB1800802)
- DOI：10.11959/j.issn.1000-0801.2022163
  中图分类号： TP393
- 网络出版日期：2022-07，
  
  纸质出版日期：2022-07-20
- 稿件说明：
移动端阅览
谷志群, 张佳玮, 纪越峰, 等. 数据与模型协同驱动的智能光网络架构与关键技术[J]. 电信科学, 2022,38(7):18-30.

Zhiqun GU, Jiawei ZHANG, Yuefeng JI, et al. Network architecture and key technologies of intelligent optical networks driven by data and model[J]. Telecommunications science, 2022, 38(7): 18-30.
谷志群, 张佳玮, 纪越峰, 等. 数据与模型协同驱动的智能光网络架构与关键技术[J]. 电信科学, 2022,38(7):18-30. DOI： 10.11959/j.issn.1000-0801.2022163.

Zhiqun GU, Jiawei ZHANG, Yuefeng JI, et al. Network architecture and key technologies of intelligent optical networks driven by data and model[J]. Telecommunications science, 2022, 38(7): 18-30. DOI： 10.11959/j.issn.1000-0801.2022163.

摘要

网络的规模升级和超大连接、超高带宽、超低时延应用的不断深化，对光传输网络资源利用和网络差异化服务提出了更高要求，使得传统模型驱动下的网络形态和配置方式面临挑战。基于数据与模型协同驱动思想，提出“3层3循环”架构及其“3可功能”特征的智能光网络技术方案，并对智能化实现技术展开研究，通过开发设计的智能传输网络平台对所提算法的性能进行测试，经验证，数据与模型协同驱动的智能光网络传输性能得到有效提升，为实现网络智能化提供了理论技术支撑。

Abstract

With the expanding scale of the networks and the emerging applications of ultra-massive connection

ultra-high bandwidth and ultra-low delay

higher requirements are proposed for the utilization of optical transmission network resources and network differentiated services

which makes the network and configuration mode driven by the traditional approaches face challenges.Based on the idea of data and model collaborative driving

the intelligent optical network technologies of three-layerthree-cycle architecture and three functions were proposed

and the implementation technology was studied.The performance of the proposed algorithms was evaluated based on the designed intelligent transmission network platform.The validation results show that the transmission performance of intelligent optical network driven by collaborative data and model has been effectively improved

which provides theoretical and technical support for the realization of network intelligence.

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