QoE-Driven Adaptive K-Push for HTTP/2 Live Streaming

Dynamic adaptive streaming (DAS) over HTTP has been widely deployed over the Internet. However, due to the <italic>pull-based</italic> nature of HTTP/1.1, there exists intolerable streaming latency and high request overhead in the current DAS systems. With dynamic <italic>k-push</italic>, HTTP/2 live streaming promises to achieve low live latency with less overhead and small segment duration. In this paper, we propose a quality of experience (QoE) driven adaptive <italic>k-push</italic> mechanism (QK-Push) for HTTP/2 live streaming. The client just sends one request to set push length (<inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>) and bitrate (<bold>v</bold>) parameters and the server would push back <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> segments in a batch. To determine <italic>k-push</italic> parameters, a probabilistic buffer model is first designed to avoid buffer underflow/overflow. Also, three QoE objective functions are designed to ensure the high streaming quality (bitrate), playback continuity, and smoothness. QK-Push casts this multi-objective optimization problem as a <italic>Pareto optimal problem</italic>. To solve it, a <italic>Nash bargaining solution</italic> is designed to balance the needs for video quality, bitrate smoothness, and request overhead. Finally, the segments in each push cycle are selected by solving the <italic>Nash problem</italic> with a <italic>discrete space Lagrangian</italic> method. We implement an HTTP/2 live streaming prototype system, with the QK-Push algorithm over modified <italic>dash.js</italic> and media presentation description. To evaluate the performances, the extensive live streaming experiments are carried out over a controllable network test bed and real Internet trace. The results demonstrate that the proposed QK-Push algorithm is able to improve the average bitrate up to 13%, reduce the bitrate oscillations up to 81%, decrease the startup delay up to 58%, and increase the estimate the mean opinion score up to 12% compared to the current HTTP/1.1 system.

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