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Bandwidth Prediction in Low-Latency Chunked Streaming

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Bandwidth Prediction in Low-Latency Chunked Streaming

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HTTP adaptive streaming (HAS) with chunked transfer encoding can be used to reduce latency without sacrificing the coding ef- ficiency. While this allows a media segment to be generated and delivered at the same time, it also causes grossly inaccurate band- width measurements, leading to incorrect bitrate selections. To overcome this effect, we design a novel Adaptive bitrate scheme for Chunked Transfer Encoding (ACTE) that leverages the unique nature of chunk downloads. It uses a sliding window to accurately measure the available bandwidth and an online linear adaptive filter to predict the available bandwidth into the future. Results show that ACTE achieves 96% measurement accuracy, which translates to a 64% reduction in stalls and a 27% increase in video quality.

HTTP adaptive streaming (HAS) with chunked transfer encoding can be used to reduce latency without sacrificing the coding ef- ficiency. While this allows a media segment to be generated and delivered at the same time, it also causes grossly inaccurate band- width measurements, leading to incorrect bitrate selections. To overcome this effect, we design a novel Adaptive bitrate scheme for Chunked Transfer Encoding (ACTE) that leverages the unique nature of chunk downloads. It uses a sliding window to accurately measure the available bandwidth and an online linear adaptive filter to predict the available bandwidth into the future. Results show that ACTE achieves 96% measurement accuracy, which translates to a 64% reduction in stalls and a 27% increase in video quality.

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