实用的AP分类器的全网包行为识别

Huazhe Wang, Chen Qian, Ye Yu, Hongkun Yang, S. Lam
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引用次数: 8

摘要

识别报文在全网范围内的转发行为对于许多网络管理应用来说是必不可少的,包括规则验证、策略实施、攻击检测、流量工程和故障定位。当前可以执行数据包行为识别的工具要么花费大量时间和内存,要么不支持实时更新。在本文中,我们提出了AP分类器,一个用于数据包行为识别的控制平面工具。AP分类器是基于原子谓词的概念开发的,原子谓词可以用来描述数据包的转发行为。使用两个真实网络的数据平面网络状态进行的实验表明,AP分类器的处理速度比现有工具至少快一个数量级。此外,AP分类器使用非常小的内存,并且能够支持实时更新。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Practical network-wide packet behavior identification by AP classifier
Identifying the network-wide forwarding behaviors of a packet is essential for many network management applications, including rule verification, policy enforcement, attack detection, traffic engineering, and fault localization. Current tools that can perform packet behavior identification either incur large time and memory costs or do not support real-time updates. In this paper we present AP Classifier, a control plane tool for packet behavior identification. AP Classifier is developed based on the concept of atomic predicates which can be used to characterize the forwarding behaviors of packets. Experiments using the data plane network state of two real networks show that the processing speed of AP Classifier is faster than existing tools by at least an order of magnitude. Furthermore, AP Classifier uses very small memory and is able to support real-time updates.
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