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.
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arxiv.org
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