Zakaria Ye

Backward-shifted strategies based on SVC for HTTP adaptive video streaming

Although HTTP-based video streaming can easily penetrate firewalls and profit from Web caches, the underlying TCP may introduce large delays in case of a sudden capacity loss. To avoid an interruption of the video stream in such cases we propose the Backward-Shifted Coding (BSC). Based on Scalable Video Coding (SVC), BSC adds a time-shifted layer of redundancy to the video stream such that future frames are downloaded at any instant. This pre-fetched content maintains a fluent video stream even under highly variant network conditions and leads to high Quality of Experience (QoE). We characterize this QoE gain by analyzing initial buffering time, re-buffering time and content resolution using the Ballot theorem. The probability generating functions of the playback interruption and of the initial buffering latency are provided in closed form. We further compute the quasi-stationary distribution of the video quality, in order to compute the average quality, as well as temporal variability in video quality. Employing these analytic results to optimize QoE shows interesting trade-offs and video streaming at outstanding fluency.

Analysis and modelling Quality of Experience of video streaming under time-varying bandwidth

We take an analytical approach to study the Quality of user Experience (QoE) for video streaming applications. Our propose is to characterise buffer starvations for streaming video in the presence of bandwidth that varies over time. This variation of the bandwidth is caused due to the frequent changes of channel states and mobility. Specifically we develop an analytical framework to investigate Quality of user Experience (QoE) for streaming by considering a Markov Modulated Fluid Model (MMFM) that accurately approximates the nature of network traffic. We drive the close-form expressions for calculating the distribution of starvation as well as start-up delay using partial differential equations (PDEs) and solve them using the Laplace Transform. We illustrate the results with the cases of the two-state Markov Modulated Fluid Model that is commonly used in multimedia applications. We compare our analytical model with simulation results using ns-3 under various operating parameters. Finally, we apply our analysis results to optimize the objective quality of experience (QoE) of media streaming realizing the tradeoff among different metrics incorporating user preferences on buffering ratio, startup delay and perceived quality.

Bitrate adaptation in backward-shifted coding for HTTP adaptive video streaming

HTTP Adaptive Streaming is able to dynamically match video quality to variable network conditions. This is a key feature for multimedia delivery when quality of service cannot be granted network-wide. For instance, the end-to-end throughput towards mobile terminals may suffer short term fluctuations due to fading. Hence, robust bitrate adaptation schemes become crucial in order to avoid degraded video reproduction. The objective, in this context, is to control the filling level of the playback buffer, maximize the video quality, and avoid unnecessary quality variations which may also impair the perceived quality of experience. In this work we study bitrate adaptation algorithms leveraging on Backward-Shifted Coding (BSC), a scalable video coding scheme able to cope with the effects of end-to-end throughput fluctuations. We have proposed a new adaptation scheme able to balance video rate smoothness and high network capacity utilization. Both the throughput-based and buffer-based variants of such scheme have been designed. Extensive simulations using synthetic and real-world video traffic traces show that the proposed solution performs remarkably well even under challenging network conditions.

Video streaming analysis in Vienna LTE system level simulator

The demand for multimedia services in mobile communication is increasing day by day due to the proliferation of end devices. To overcome the future needs of data communication on mobile devices, the 3rd Generation Partnership Project (3GPP) has introduced a new technology which is known as Long Term Evolution (LTE) UMTS. In this paper, we study video streaming behavior on the LTE network. For this purpose, we use the Vienna LTE System Level Simulator which implements network features that correspond to our goal. We consider the parameters that may affect the users experience on a network and define ten scenarios for our simulations. We finally search for methods to fit the video streaming data traffic on the LTE network and exhibit its long range dependence.

Quality of Experience in HTTP Adaptive Video Streaming Systems

The main task of HTTP Adaptive Streaming (HAS) is to adapt video quality dynamically under variable network conditions. This is a key feature for multimedia delivery especially when quality of service cannot be granted network-wide and, e.g., throughput may suffer short term fluctuations. Hence, robust bitrate adaptation schemes become crucial in order to improve video quality of experience. The objective, in this context, is to control the filling level of the playback buffer and maximize the quality of the video, while avoiding unnecessary video quality variations. In this paper we study bitrate adaptation algorithms based on Backward-Shifted Coding (BSC), a scalable video coding scheme able to greatly improve video quality of experience. We design bitrate adaptation algorithms that balance video rate smoothness and high network capacity utilization, leveraging both on throughput-based and buffer-based adaptation mechanisms. Extensive simulations using an MPEG/DASH client server application on ns-3 show that the proposed scheme performs remarkably well even under challenging network conditions.