HTTP adaptive streaming is increasingly popular in multimedia delivery nowadays. The nature of HTTP provides easy deployment to content provider and chunk-based delivery enables dynamic adaption of video quality to varying network bandwidth. In this paper, we address two topics in HTTP adaptive streaming. First is the impact of bitrate disparity. In the previous work, it shows that the advertised bitrates by manifest file and the actual bitrates are significantly different. The result of inaccurate estimation causes buffer oscillations or even buffer underrun because clients frequently select higher bitrates than the network bandwidth. To employ the extensibility feature of DASH syntax, we present a systematic method for selecting the segment which real bitrate is the closest one to the given estimated throughput. The second topic is the well-known bandwidth competition on the bottleneck. We adopt logistic function to estimate bandwidth while using it to detect occurrences of bandwidth oscillations due to competition. We propose an algorithm written on client side to stabilize the requested bitrates in competition interval. The experiments show that our solutions stabilize client behavior in competition state and streaming with real bitrates improves buffer oscillations.

HTTP adaptive streaming is increasingly popular in multimedia delivery nowadays. The nature of HTTP provides easy deployment to content provider and chunk-based delivery enables dynamic adaption of video quality to varying network bandwidth. In this paper, we address two topics in HTTP adaptive streaming. First is the impact of bitrate disparity. In the previous work, it shows that the advertised bitrates by manifest file and the actual bitrates are significantly different. The result of inaccurate estimation causes buffer oscillations or even buffer underrun because clients frequently select higher bitrates than the network bandwidth. To employ the extensibility feature of DASH syntax, we present a systematic method for selecting the segment which real bitrate is the closest one to the given estimated throughput. The second topic is the well-known bandwidth competition on the bottleneck. We adopt logistic function to estimate bandwidth while using it to detect occurrences of bandwidth oscillations due to competition. We propose an algorithm written on client side to stabilize the requested bitrates in competition interval. The experiments show that our solutions stabilize client behavior in competition state and streaming with real bitrates improves buffer oscillations.

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