Traffic Weaver is a Python package developed to generate a semi-synthetic signal (time series) with finer granularity, based on averaged time series, in a manner that, upon averaging, closely matches the original signal provided. The key components utilized to recreate the signal encompass oversampling with a given strategy, stretching to match the integral of the original time series, smoothing, repeating, applying trend, and adding noise. The primary motivation behind Traffic Weaver is to furnish semi-synthetic time-varying traffic in telecommunication networks, facilitating the development and validation of traffic prediction models, as well as aiding in the deployment of network optimization algorithms tailored for time-varying traffic.
@article{arxiv.2403.11388,
title = {Traffic Weaver: semi-synthetic time-varying traffic generator based on averaged time series},
author = {Piotr Lechowicz and Aleksandra Knapińska and Adam Włodarczyk and Krzysztof Walkowiak},
journal= {arXiv preprint arXiv:2403.11388},
year = {2024}
}