tpprof: A Network Traffic Pattern Profiler
tpprof: A Network Traffic Pattern Profiler
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发表时间：
2020
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通讯作者：
Nofel Yaseen;John Sonchack;Vincent Liu
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作者：
Nofel Yaseen;John Sonchack;Vincent Liu
在设计、理解或优化计算机网络时，识别和排列随着时间的推移其使用中的常见模式通常是有用的。通常被称为网络流量模式，识别网络花费大部分时间的模式可以帮助网络运营商大大减轻任务。尽管如此，不幸的是，从网络中提取交通模式是一个困难且高度手动的过程。在本文中，我们介绍了tpprof，一个网络流量模式的分析器。tpprof是围绕两个新颖的抽象构建的：（1）网络状态，其捕获网络链路利用率的近似快照;以及（2）交通模式子序列，其表示网络状态序列上的有限状态自动机。围绕这些抽象，我们介绍了新的技术来提取这些抽象，一个强大的工具来分析它们，并提醒运营商在运行的网络中存在的系统。
When designing, understanding, or optimizing a computer network, it is often useful to identify and rank common patterns in its usage over time. Often referred to as a network traffic pattern, identifying the patterns in which the network spends most of its time can help ease network operators’ tasks considerably. Despite this, extracting traffic patterns from a network is, unfortunately, a difficult and highly manual process. In this paper, we introduce tpprof , a profiler for network traffic patterns. tpprof is built around two novel abstractions: (1) network states, which capture an approximate snap-shot of network link utilization and (2) traffic pattern sub-sequences,which represent a finite-state automaton over a sequence of network states. Around these abstractions, we introduce novel techniques to extract these abstractions, a robust tool to analyze them, and a system for alerting operators of their presence in a running network.