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.

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This work is licensed under a Creative Commons Attribution 4.0 License.