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• W4226161973 abstract "In today's Internet, bandwidth dynamics are inevitable, and hence, the bitrate for live streaming applications should also be dynamically adjusted. However, in existing HTTP-based adaptive streaming (HAS), bitrate switching can only be performed at segment boundaries, making decisions unresponsive and often inaccurate. In this paper, we start from a close investigation on the impact of the segment length in HAS and accordingly present VHAS, an extension towards intelligent variable-length segmentation, which makes client-side decisions based on the massive amount of real-time information from the network and viewers. VHAS implements a smart trigger mechanism that balances accuracy and overhead for variable-length segmentation. We further develop an adaptive bitrate switching algorithm with data-driven I-frame prediction, which is tailored to individual viewers to minimize bitrate mismatches. We evaluate VHAS via extensive trace-driven simulations, and our results demonstrate that compared with state-of-the-art solutions, VHAS achieves 15% - 49% gains in QoE, with a noticeable bandwidth reduction of 37% - 57%." @default.
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• W4226161973 date "2023-01-01" @default.
• W4226161973 modified "2023-10-17" @default.
• W4226161973 title "Timely and Accurate Bitrate Switching in HTTP Adaptive Streaming with Date-Driven I-frame Prediction" @default.
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• W4226161973 doi "https://doi.org/10.1109/tmm.2022.3165381" @default.
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