Adaptive video streaming using HTTP has become popular in recent years for commercial video delivery. The recent MPEG-DASH standard allows interoperability and adaptability between servers and clients from different vendors. The delivery of the MPD (Media Presentation Description) files in DASH and the DASH client behaviours are beyond the scope of the DASH standard. However, the different adaptation algorithms employed by the clients do affect the overall performance of the system and users’ QoE (Quality of Experience), hence the need for research in this field. Moreover, standard DASH delivery is based on fixed segments of the video. However, there is no standard segment duration for DASH where various fixed segment durations have been employed by different commercial solutions and researchers with their own individual merits. Most recently, the use of variable segment duration in DASH has emerged but only a few preliminary studies without practical implementation exist. In addition, such a technique requires a DASH client to be aware of segment duration variations, and this requirement and the corresponding implications on the DASH system design have not been investigated. This paper proposes a segment-duration-aware bandwidth estimation and next-segment selection adaptation strategy for DASH. Firstly, an MPD file extension scheme to support variable segment duration is proposed and implemented in a realistic hardware testbed. The scheme is tested on a DASH client, and the tests and analysis have led to an insight on the time to download next segment and the buffer behaviour when fetching and switching between segments of different playback durations. Issues like sustained buffering when switching between segments of different durations and slow response to changing network conditions are highlighted and investigated. An enhanced adaptation algorithm is then proposed to accurately estimate the bandwidth and precisely determine the time to download the next optimal segment considering the variable segment duration. Furthermore, objective metrics are employed to highlight the merits of the achieved compression efficiency using longer segment sizes for higher bitrate representations.
The Dynamic Adaptive Streaming over HTTP (DASH) standard is becoming increasingly popular for real-time adaptive
HTTP streaming of internet video in response to unstable network conditions. Integration of DASH streaming techniques
with the new H.265/HEVC video coding standard is a promising area of research. The performance of HEVC-DASH
systems has been previously evaluated by a few researchers using objective metrics, however subjective evaluation
would provide a better measure of the user’s Quality of Experience (QoE) and overall performance of the system.
This paper presents a subjective evaluation of an HEVC-DASH system implemented in a hardware testbed. Previous
studies in this area have focused on using the current H.264/AVC (Advanced Video Coding) or H.264/SVC (Scalable
Video Coding) codecs and moreover, there has been no established standard test procedure for the subjective evaluation
of DASH adaptive streaming. In this paper, we define a test plan for HEVC-DASH with a carefully justified data set
employing longer video sequences that would be sufficient to demonstrate the bitrate switching operations in response to
various network condition patterns. We evaluate the end user’s real-time QoE online by investigating the perceived
impact of delay, different packet loss rates, fluctuating bandwidth, and the perceived quality of using different DASH
video stream segment sizes on a video streaming session using different video sequences. The Mean Opinion Score
(MOS) results give an insight into the performance of the system and expectation of the users. The results from this
study show the impact of different network impairments and different video segments on users’ QoE and further analysis
and study may help in optimizing system performance.
Real-time HTTP streaming has gained global popularity for delivering video content over Internet. In particular, the recent MPEG-DASH (Dynamic Adaptive Streaming over HTTP) standard enables on-demand, live, and adaptive Internet streaming in response to network bandwidth fluctuations. Meanwhile, emerging is the new-generation video coding standard, H.265/HEVC (High Efficiency Video Coding) promises to reduce the bandwidth requirement by 50% at the same video quality when compared with the current H.264/AVC standard. However, little existing work has addressed the integration of the DASH and HEVC standards, let alone empirical performance evaluation of such systems. This paper presents an experimental HEVC-DASH system, which is a pull-based adaptive streaming solution that delivers HEVC-coded video content through conventional HTTP servers where the client switches to its desired quality, resolution or bitrate based on the available network bandwidth. Previous studies in DASH have focused on H.264/AVC, whereas we present an empirical evaluation of the HEVC-DASH system by implementing a real-world test bed, which consists of an Apache HTTP Server with GPAC, an MP4Client (GPAC) with open HEVC-based DASH client and a NETEM box in the middle emulating different network conditions. We investigate and analyze the performance of HEVC-DASH by exploring the impact of various network conditions such as packet loss, bandwidth and delay on video quality. Furthermore, we compare the Intra and Random Access profiles of HEVC coding with the Intra profile of H.264/AVC when the correspondingly encoded video is streamed with DASH. Finally, we explore the correlation among the quality metrics and network conditions, and empirically establish under which conditions the different codecs can provide satisfactory performance.