Application-Awareness in SDN

被引：114

作者：

Qazi, Zafar ^{[1
]}

Lee, Jeongkeun

Jin, Tao

Bellala, Gowtham

Arndt, Manfred

Noubir, Guevara ^{[2
]}

机构：

[1] SUNY Stony Brook, Stony Brook, NY 11790 USA

[2] Northeastern Univ, Boston, MA USA

来源：

ACM SIGCOMM COMPUTER COMMUNICATION REVIEW | 2013年 / 43卷 / 04期

关键词：

Software-Defined Networking (SDN); Application Awareness;

D O I：

10.1145/2534169.2491700

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present a framework, Atlas, which incorporates application-awareness into Software-Defined Networking (SDN), which is currently capable of L2/3/4-based policy enforcement but agnostic to higher layers. Atlas enables fine-grained, accurate and scalable application classification in SDN. It employs a machine learning (ML) based traffic classification technique, a crowd-sourcing approach to obtain ground truth data and leverages SDN's data reporting mechanism and centralized control. We prototype Atlas on HP Labs wireless networks and observe 94% accuracy on average, for top 40 Android applications.

引用

页码：487 / 488

页数：2