# Data center TCP dataset

## TL;DR

This paper introduces a comprehensive dataset of TCP network flows in data centers, useful for comparing TCP versions and developing machine learning models.

## Contribution

The paper presents a unique dataset comparing 17 TCP versions with different congestion control algorithms.

## Key findings

- The dataset includes 50 measurements per TCP flow to ensure stability.
- 18 quantitative attributes are used to compare TCP versions.
- The dataset supports testing, optimization, and machine learning model development for TCP.

## Abstract

In this paper, we would like to introduce a unique dataset that covers thousands of network flow measurements realized through TCP in a data center environment. The TCP protocol is widely used for reliable data transfers and has many different versions. The various versions of TCP are specific in how they deal with link congestion through the congestion control algorithm (CCA). Our dataset represents a unique, comprehensive comparison of the 17 currently used versions of TCP with different CCAs. Each TCP flow was measured precisely 50 times to eliminate the measurement instability. The comparison of the various TCP versions is based on the knowledge of 18 quantitative attributes representing the parameters of a TCP transmission. Our dataset is suitable for testing and comparing different versions of TCP, creating new CCAs based on machine learning models, or creating and testing machine learning models, allowing the identification and optimization of the currently existing versions of TCP.