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

Dalia El-Banna, Taufiq Asyhari
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Abstract

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.
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基于熵的下一代网络视频传输帧排除框架
随着视讯流量日益增加,以及用户对可接受的视讯质素的期望越来越高,如何在达到用户体验质素的同时,最大限度地利用网络资源,以避免网络服务供应商的潜在收入损失,已成为一项挑战。传统的允许控制(AC)算法在实现感知的QoE和允许的视频会话数量之间的平衡方面存在许多局限性。本文提出了一种新的框架,该框架利用视频流量特征来提供一种自适应的准入控制技术,而不影响视频流量的感知QoE。更具体地说,我们应用信息理论工具,即信息熵,对输入的视频信号进行帧选择。实验结果突出了研究框架的前景,并确定了可能的未来应用。
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