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Entropy Based Frame Exclusion Framework for Video Transmission over Next Generation Networks

机译:基于熵的帧排除框架,用于下一代网络的视频传输

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With the growing increase of the video traffic and the increasing expectations of users in terms of the acceptable video quality, achieving the users' Quality of Experience (QoE) while maximising the network resource utilisation to avoid any potential loss of revenue for the ISPs had become a challenge. Traditional Admission Control (AC) algorithms have many limitations in terms of achieving the balance between the perceived QoE and the number of admitted video sessions. This paper proposes a novel framework that exploits video traffic characteristics to present an adaptive admission control technique without compromising the perceived QoE for video traffic. More specifically, we apply an information theoretic tool, namely information entropy, to perform frame selection to the incoming video signals. Experiment results highlight the promise of the studied framework and identify possible future applications.
机译:随着视频流量增长的增加和用户在可接受的视频质量方面的增加,实现了用户的体验质量(QoE),同时最大化网络资源利用,以避免任何潜在的ISP收入损失一个挑战。传统的入学控制(AC)算法在实现QoE之间的平衡和录取的视频会话数量之间具有许多限制。本文提出了一种新颖的框架,该框架利用视频流量特性来呈现自适应准入控制技术,而不会损害对视频流量的感知QoE。更具体地,我们应用信息理论工具,即信息熵,对输入视频信号执行帧选择。实验结果突出了研究框架的承诺,并确定了未来可能的应用程序。

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