Dynamic Flow Entry Timeouts Based Packet Nonuniform Sampling for Elephant Flow Detection

Ling Xia Liao, Xiaohang Ma, Zhi Li, Han-Chieh Chao
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Abstract

This paper proposes a controller-based elephant detection approach based on packet statistics sampled by dynamic timeouts of flow entries. It avoids transporting statistics generated at switches to controllers by directly counting statistics using the packets forwarded to controllers for the installation and reactivation of entries. By initializing entries with hard timeout of 0.008s, and keeping doubling it whenever the entries timed out until flows are detected as elephants or out of life spans (the timeouts of flow entries of flows that have been detected as elephants are switched to idle timeout of 5s), the approach achieves a detection accuracy around 90% while reducing the bandwidth usage to less than 30% of the original over packet traces caught from the same network. By giving various initial timeout adjustment strategy to TCP and UDP flows, the approach can maintain the same high detection accuracy and low bandwidth usage over various networks.
大象流检测中基于动态流入口超时的数据包非均匀采样
本文提出了一种基于控制器的大象检测方法,该方法基于流项动态超时采样的数据包统计信息。它通过使用转发到控制器的用于安装和重新激活条目的数据包直接计数统计信息,避免了将交换机生成的统计信息传输到控制器。通过初始化硬超时为0.008秒的条目,并在条目超时时将其加倍,直到将流检测为大象或超出生命周期(将已检测为大象的流的流条目的超时切换为5秒的空闲超时),该方法实现了大约90%的检测精度,同时将带宽使用减少到低于从同一网络捕获的原始数据包跟踪的30%。该方法通过对TCP和UDP流给出不同的初始超时调整策略,可以在不同的网络中保持相同的高检测精度和低带宽占用。
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