Intelligent Algorithm for Enhancing MPEG-DASH QoE in eMBMS

Abstract

Multimedia streaming is the most demanding and bandwidth hungry application in today's world of Internet. MPEG-DASH as a video technology standard is designed for live or on-demand streams in Internet to deliver better quality content with the fewest dropouts and least possible buffering. Hybrid architecture of DASH and eMBMS have attracted a great attention from the telecommunication industry and multimedia services. It is employed in response to the immense demand of multimedia traffic. However, handover and limited resources are highly affected when they lose segments of the adaptive video streaming while the users are receiving the eMBMS service. It is a problem for service and network providers when they deliver the service because it produces an adverse impact on Quality of Experience (QoE). In this paper, we show a case study to evaluate MPEG-DASH QoE in eMBMS service, by measuring the Quality of Service (QoS) metrics that influence the QoE. We observe the objective metrics like stalling (number, duration and place), buffer length and accumulative video time to assess the QoE. A smart algorithm is developed to predict the rate of the lost segments in multicast adaptive video streaming. The algorithm uses an estimation decision to recover the lost segments from one of the content providers. According to the obtained results based on our proposed algorithm, the user perceived latency is highly decreased in comparison to the traditional approach of MPEG-DASH multicast and unicast when there is high number of users.

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