A Survey of Traffic Classification in Software Defined Networks

被引:0
|
作者
Yan, Jinghua [1 ]
Yuan, Jing [1 ]
机构
[1] Natl Comp Network Emergency Response Tech Team, Coordinat Ctr China, Beijing, Peoples R China
来源
PROCEEDINGS OF 2018 1ST IEEE INTERNATIONAL CONFERENCE ON HOT INFORMATION-CENTRIC NETWORKING (HOTICN 2018) | 2018年
基金
中国国家自然科学基金;
关键词
Software defined networks; traffic classification; machine learning; FEATURE-SELECTION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Traffic classification has been widely used in network management, service measurements, network design, security monitoring and advertising. Software defined networks (SDN) is an newly-developing technology, which is capable of address problems in the traditional network by simplifying network management, introducing network programmability, and providing a global view of a network. Recent years, SDN has brought new opportunity to classify traffic. Traffic classification techniques in SDN have been investigated, proposed and developed. This paper looks at emerging research into the traffic classification techniques in SDN. We first introduce SDN and related work of traffic classification, and then review several representative works of traffic classification in SDN. These works are reviewed in line with the choice of classification strategies and contribution to the literature. Research challenges and future directions for SDN traffic classification are also discussed.
引用
收藏
页码:200 / 206
页数:7
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