# Flow length and size distributions in campus Internet traffic

arXiv: https://arxiv.org/abs/1809.03486 · HTML: https://mlsanity.com/paper/1809.03486/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Sep 2018.

## Built on by (most cited first, 4 of 4)

- [Brain-on-Switch: Towards Advanced Intelligent Network Data Plane via NN-Driven Traffic Analysis at Line-Speed](https://mlsanity.com/paper/2403.11090/) (2024)
- [RouteNet-Gauss: Hardware-Enhanced Network Modeling with Machine Learning](https://mlsanity.com/paper/2501.08848/) (2025)
- [Temporal Analysis of NetFlow Datasets for Network Intrusion Detection Systems](https://mlsanity.com/paper/2503.04404/) (2025)
- [Traffic-Aware Service Relocation in Cloud-Oriented Elastic Optical Networks](https://mlsanity.com/paper/2105.07653/) (2021)

## Abstract (arXiv)

The efficiency of flow-based networking mechanisms strongly depends on traffic characteristics and should thus be assessed using accurate flow models. For example, in the case of algorithms based on the distinction between elephant and mice flows, it is extremely important to ensure realistic flows' length and size distributions. Credible models or data are not available in literature. Numerous works contain only plots roughly presenting empirical distribution of selected flow parameters, without providing distribution mixture models or any reusable numerical data. This paper aims to fill that gap and provide reusable models of flow length and size derived from real traffic traces. Traces were collected at the Internet-facing interface of the university campus network and comprise four billion layer-4 flow (275 TB). These models can be used to assess a variety of flow-oriented solutions under the assumption of realistic conditions. Additionally, this paper provides a tutorial on constructing network flow models from traffic traces. The proposed methodology is universal and can be applied to traffic traces gathered in any network. We also provide an open source software framework to analyze flow traces and fit general mixture models to them.