Abstract
The current Dynamic Bandwidth Selection (DBS) algorithm only uses a snapshot of client metrics to make bandwidth recommendations for the remainder of the day. According to the present techniques, machine learning (ML) may be used to track/predict bias factors for DBS throughout the day.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Kulkarni, Santosh; Desai, Vishal; Choi, Young II; and Monajemi, Pooya, "RADIOFREQUENCY TRENDS AWARE DYNAMIC BANDWIDTH SELECTION", Technical Disclosure Commons, (January 30, 2019)
https://www.tdcommons.org/dpubs_series/1922
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