.png){kind=icon}
返回
A fair server adaptation algorithm for HTTP adaptive streaming using video complexity
.png){kind=icon}
PRE
AI
DOI：10.1007/s11042-018-6615-z.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The increasing popularity of online video content and adaptive video streaming services, especially those based on HTTP Adaptive Streaming (HAS) highlights the need for streaming optimization solutions. From a server perspective, the main drawback of HAS is that the user selects the quality of the next video segment without taking the server constraints into account. These constraints include the number of users simultaneously being served and the server's congestion. Here, we present the Fair Server Adaptation (FSA) algorithm, which is designed to maximize user Quality of Experience (QoE) by tackling the server's bottleneck problem. The algorithm provides the quality representation that is closest to the user's request, subject to the server's constraints. Simulation results show that compared to standard Dynamic Adaptive Streaming over HTTP (DASH) server, FSA increased the number of served users and decreased both the number of rebuffering events and the average rebuffering event duration. Furthermore, the average number of unserved users decreased to almost zero and Jain's fairness index rose. It is clear that these changes increase users' QoE.
Keyword:
Dynamic adaptive streaming over HTTP
Video streaming optimization
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3
论文数:
1.9W
被引数:
3.2W
机构
引用论文
Design and optimisation of a (FA)Q-learning-based HTTP adaptive streaming client.png)
CONNECTION SCIENCE
OAAI
CONNECTION SCIENCEIF3.4
OAAI分享收藏分享收藏
查看更多内容