Traffic weaver: Semi-synthetic time-varying traffic generator based on averaged time series
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 generate the signal encompass oversampling, recreating from average with a given strategy, stretching to match the integral of the original time series, interpolating, 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.
Authors
- Krzysztof Walkowiak (ORCID: https://orcid.org/0000-0003-1686-3110)
- Piotr Lechowicz (ORCID: https://orcid.org/0000-0003-2555-5187)
- Aleksandra Knapińska (ORCID: https://orcid.org/0000-0003-2654-4893)
- Adam Włodarczyk (ORCID: https://orcid.org/0000-0001-6649-6318)
Institutions
- Wrocław University of Science and Technology (PL)
- Chalmers University of Technology (SE)
- AGH University of Krakow (PL)
Publication Details
- Journal
- SoftwareX
- Published
- 2024-10-31
- DOI
- https://doi.org/10.1016/j.softx.2024.101946
- Citations
- 4
- Primary Topic
- Network Security and Intrusion Detection
- Type
- article
- Field-Weighted Citation Impact
- 1.40
Funders
- Narodowe Centrum Nauki
- Narodowym Centrum Nauki