通信学报 ›› 2019, Vol. 40 ›› Issue (11): 171-179.doi: 10.11959/j.issn.1000-436x.2019229

• 杰青优青专栏 • 上一篇    下一篇

基于深度学习的面向IP-over-EON的可编程跨层网络业务性能感知系统

朱祖勍,孔嘉伟,牛彬,唐绍飞,房红强,刘思祺   

  1. 中国科学技术大学信息科学技术学院,安徽 合肥 230027
  • 修回日期:2019-10-17 出版日期:2019-11-25 发布日期:2019-12-06
  • 作者简介:朱祖勍(1979- ),男,安徽蚌埠人,博士,中国科学技术大学教授,主要研究方向为下一代网络体系架构、云计算和光通信网络以及多媒体网络。|孔嘉伟(1995- ),男,安徽六安人,中国科学技术大学硕士生,主要研究方向为光通信网络。|牛彬(1994- ),男,安徽阜阳人,中国科学技术大学硕士生,主要研究方向为下一代网络体系架构。|唐绍飞(1995- ),男,安徽铜陵人,中国科学技术大学硕士生,主要研究方向为下一代网络体系架构。|房红强(1995- ),男,安徽阜阳人,中国科学技术大学硕士生,主要研究方向为光通信网络和机器学习。|刘思琪(1993- ),男,河南新乡人,中国科学技术大学博士生,主要研究方向为光通信网络和机器学习。
  • 基金资助:
    国家自然科学基金资助项目(61871357);国家自然科学基金资助项目(61771445);国家自然科学基金资助项目(61701472)

DL-assisted programmable multilayer network application awareness system for IP-over-EON

Zuqing ZHU,Jiawei KONG,Bin NIU,Shaofei TANG,Hongqiang FANG,Siqi LIU   

  1. School of Information Science and Technology,University of Science and Technology of China,Hefei 230027,China
  • Revised:2019-10-17 Online:2019-11-25 Published:2019-12-06
  • Supported by:
    The National Natural Science Foundation of China(61871357);The National Natural Science Foundation of China(61771445);The National Natural Science Foundation of China(61701472)

摘要:

为了实现实时的、细粒度的网络性能监测与调整,并且满足不同应用的特定服务质量需求,提出了基于深度学习的面向IP-over-EON的可编程跨层网络业务性能感知系统。该系统将基于网络业务性能感知的分布式网络监测与集中式网络管控相结合,分布式网络监测实现跨层和细粒度的网络监控,并基于深度学习进行数据分析。实验结果表明,该系统通过有机地结合集中式与分布式的处理方式,实现了及时的、自动化的网络控制与管理,具有良好的可扩展性。

关键词: 深度学习, 弹性光网络, 跨层带内网络遥测, 网络异常监测与定位

Abstract:

In order to realize real-time and fine-granularity network monitoring and adjustment,and satisfy the specific QoS demands of various applications,a deep learning (DL) assisted programmable multilayer network application performance awareness system for IP-over-EON was proposed.The distributed network monitoring based on network application performance awareness was combined with centralized network management.The multilayer and fine-grained network monitoring was implemented by distributed network monitoring,and the data analysis through DL was performed.Experimental results indicate that by combining distributed and centralized processing seamlessly,the proposed network monitoring system can not only realize timely and automatic network control and management but also provide superior scalability.

Key words: deep learning, elastic optical network, multi-layer in-band network telemetry

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