Dynamic Buffer Lookahead in Adaptive Streaming Using Machine Learning

Abstract

A method and system for adaptive video streaming receives inputs by a deep learning neural network engine. The inputs may include a previous lookahead buffer size, previous download time(s), a current buffer size, next available stream size(s), a last chuck quality, a current buffer size, previous download speed(s), a previous lookahead buffer size, a number of chunks remaining, and/or network condition statistics based upon geolocation information. The inputs are processed by the deep learning neural network engine using a neural network machine learning model to adjust a capacity of a buffer lookahead.

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