Adaptive SDN-based architecture using QoE metrics in live video streaming on Cloud Mobile Media

M. García-Pineda, Santiago Felici-Castell, Jaume Segura-García
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引用次数: 9

Abstract

The increasing adoption of smart phones, the increased access to mobile broadband networks and the availability of public cloud infrastructures are aligning to the next generation of truly ubiquitous multimedia services, known as Cloud Mobile Media (CMM) services. Nevertheless, due to an inherit higher and variable end to end delay mainly as a result of the virtualization process, new challenges appear in particular for live video streaming applications in order to keep a good Quality of Experience of the delivered video. Thus, to keep client's satisfaction at good levels in terms of Mean Opinion Score (MOS), we propose an adaptive Software Defined Networking (SDN)-based architecture running on CMM. We estimate MOS using an statistical method based on Factor Analysis (FA) and then the SDN controller is able to schedule different actions. The MOS estimation is based on different measured variables throughout the CMM infrastructure. Finally, we compare the accuracy of the estimated MOS against well known publicly available video quality algorithms as well as we propose an algorithm to run at the SDN controller to meet these requirements.
基于自适应sdn的架构,在云移动媒体上的实时视频流中使用QoE指标
智能手机的日益普及、移动宽带网络的日益普及以及公共云基础设施的可用性,正与下一代真正无处不在的多媒体服务(即云移动媒体(CMM)服务)相结合。然而,由于虚拟化过程带来了更高的端到端延迟和可变延迟,特别是对于实时视频流应用来说,为了保持交付视频的良好体验质量,出现了新的挑战。因此,为了保持客户满意度在平均意见得分(MOS)方面的良好水平,我们提出了一种基于软件定义网络(SDN)的自适应架构,该架构运行在CMM上。我们使用基于因子分析(FA)的统计方法估计MOS,然后SDN控制器能够调度不同的动作。在整个CMM基础结构中,MOS估计基于不同的测量变量。最后,我们将估计的MOS的精度与已知的公开可用的视频质量算法进行了比较,并提出了一种在SDN控制器上运行的算法来满足这些要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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