跨域场景下的联邦路由机制设计

doi:10.11959/j.issn.1000-0801.2020286

电信科学 ›› 2020, Vol. 36 ›› Issue (10): 29-36.doi: 10.11959/j.issn.1000-0801.2020286

跨域场景下的联邦路由机制设计

丛培壮¹,张宇超¹(),田野¹,王文东¹,李丹²

¹ 北京邮电大学，北京100876
² 清华大学，北京100084

修回日期:2020-10-10 出版日期:2020-10-20 发布日期:2020-11-07
作者简介:丛培壮（1994- ），男，北京邮电大学网络与交换技术国家重点实验室博士生，主要研究方向为网络体系结构、移动互联网创新服务应用等|张宇超（1989- ），女，北京邮电大学计算机学院（国家示范性软件学院）副教授、硕士生导师，主要研究方向为数据驱动网络、大规模数据中心网络、边缘计算|田野（1981- ），男，北京邮电大学网络与交换技术国家重点实验室副教授、硕士生导师，主要研究方向为下一代互联网、数据挖掘、知识发现等|王文东（1963- ），男，北京邮电大学网络与交换技术国家重点实验室教授、博士生导师，主要研究方向为网络体系结构、网络和业务的服务质量控制与管理、机器学习与移动互联网网络与应用等|李丹（1981- ），男，博士，清华大学教授、博士生导师，主要研究方向为数据中心网络、网络智能和可信任互联网。入选教育部“青年长江学者”奖励计划，获得国家优秀青年基金项目资助，国家“973”项目首席科学家，国家重点研发计划项目负责人。IEEE Transactions on Computers、IEEE Transactions on Wireless Communications等国际学术期刊编委，ACM SIGCOMM、IEEE INFOCOM等国际学术会议程序委员会委员
基金资助:
国家自然科学基金资助项目(61802024);中央高校基本科研业务费专项资金资助项目(2482020RC36);国家重点研发计划项目(2019YFB1802603)

Design of federated routing mechanism in cross-domain scenario

Peizhuang CONG¹,Yuchao ZHANG¹(),Ye TIAN¹,Wendong WANG¹,Dan LI²

¹ Beijing University of Posts and Telecommunications,Beijing 100876,China
² Tsinghua University,Beijing 100084,China

Revised:2020-10-10 Online:2020-10-20 Published:2020-11-07
Supported by:
The National Natural Science Foundation of China (NSFC) Youth Science Foundation(61802024);The Fundamental Research Funds for The Central Universities under Grant(2482020RC36);The National Key Research and Development Program of China(2019YFB1802603)

摘要/Abstract

摘要：

随着多网融合的发展，独立自治域网络之间的高效互联互通已成为一个关键理论技术问题。由于域内信息的私密性，各自治域之间不会共享相关的数据，传统的域间路由协议无法提供高效的跨域路由机制。为克服现有协议存在的不足，提出了一种基于机器学习的联邦路由机制，该机制通过各自治域的神经网络模型和参数隐式地共享域内信息，不仅可打破现存的数据孤岛问题，还可极大地减少域间信息共享所需要传输的数据量，进而降低全网路由信息收敛时延，基于该联邦路由机制，边界路由器也能够根据全网状态信息制定全局的优化路由转发策略。

关键词: 跨域网络, 联邦路由, 网络融合

Abstract:

With the development of multi-network integration,how to ensure efficient interconnections among multiple independent network domains is becoming a key problem.Traditional interdomain routing protocol fails due to the limitation of domain information privacy,where each autonomous domain doesn’t share any specific intra-domain information.A machine learning-based federated routing mechanism was proposed to overcome the existing shortcomings.Each autonomous domain shares intra-domain information implicitly via neural network models and parameters.It not only breaks data islands problems but also greatly reduces the amount of transmitted data shared between domains,then decreases convergence delay of entire network information.Based on the federated routing mechanism,border routers can formulate global optimal routing strategies according to the status of entire network.

Key words: cross-domain network, federated routing, network integration

中图分类号:

TP393

丛培壮, 张宇超, 田野, 王文东, 李丹. 跨域场景下的联邦路由机制设计[J]. 电信科学, 2020, 36(10): 29-36.

Peizhuang CONG, Yuchao ZHANG, Ye TIAN, Wendong WANG, Dan LI. Design of federated routing mechanism in cross-domain scenario[J]. Telecommunications Science, 2020, 36(10): 29-36.

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跨域场景下的联邦路由机制设计

Design of federated routing mechanism in cross-domain scenario

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