Core Concepts
Generating semi-synthetic time-varying traffic for network optimization.
Abstract
Traffic Weaver is a Python package designed to create semi-synthetic signals with finer granularity, closely matching the original signal provided. It aims to facilitate the development and validation of traffic prediction models in telecommunication networks. The software utilizes oversampling, stretching, smoothing, repeating, trend application, and noise addition to recreate the signal accurately. By generating new data based on existing samples, Traffic Weaver enables thorough evaluation of algorithms in real-world settings. The tool has been used in scientific research to develop and evaluate traffic prediction models and network optimization algorithms using generated time-varying connection requests.
Stats
Current code version: 1.3.5
Legal Code License: MIT
Software code languages: Python ≥ 3.9
Link to developer documentation/manual: http://w4k2.github.io/traffic-weaver/
Quotes
"Existing analyses of real traffic data collected by authors usually stop at the data characterization stage."
"Traffic Weaver allows easy access to data for thorough evaluation of developed algorithms."
"The software creates new datasets based on existing examples or user-specified data."