tpprof: A Network Traffic Pattern Profiler


Nofel Yaseen, John Sonchack, and Vincent Liu, University of Pennsylvania


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 snapshot 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.

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@inproceedings {246362,
author = {Nofel Yaseen and John Sonchack and Vincent Liu},
title = {tpprof: A Network Traffic Pattern Profiler },
booktitle = {17th USENIX Symposium on Networked Systems Design and Implementation (NSDI 20)},
year = {2020},
isbn = {978-1-939133-13-7},
address = {Santa Clara, CA},
pages = {1015--1030},
url = {},
publisher = {USENIX Association},
month = feb,

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