Exploiting the layer correlation to improve DASH scheduling with scalable video coding Abstract   DASH is a promising video streaming solution that gracefully deals with network throughput fluctuations as well as terminal heterogeneity. In DASH, an MPD file describes the available video qualities and their average bitrates. However, the coarsegrained average bitrate is insufficient for an accurate clientside scheduler. The bitrate overestimate or underestimate of bandwidth requirements for segments to be fetched could result in suboptimal scheduling decisions and possibly drain the playback buffer. In this paper, we first made the observation that with SVC, video segments across different layers exhibit high size correlation. We then showed that enhancement layer segment size can be predicted by the corresponding base layer segment with relatively high accuracy. Based on this observation, we enhanced existing ratebased and bufferedbased adaptive bitrate (ABR) algorithms with a size predictor, which is orthogonal to existing adaptation logics. Results show that augmented by the size predictor, the average playback bitrate can be improved by up to 20% and playback stalls can also be significantly reduced. Our results demonstrated that similar to the bandwidth predictor, a size predictor should also be added to SVCbased ABR algorithms to increase the performance gain.

Delivery of High Definition Video Content over Bandwidth Constrained Links in Heterogeneous Wireless Networks In order to deal with the fluctuations in available bandwidth that mobile users experience, modern video streaming employs adaptive bitrate (ABR) algorithms. MPEGDASH enabled clients adapt the bitrate of requested video segments to match as closely as possible the available bandwidth of the wireless link in use. If link conditions are poor or the link is congested, the ABR algorithm will select the lowest available bitrate supported by the video stream. This approach works well for standard video content since there is no restriction on using low bitrates.However, for users wishing to view High Definition (HD) content, there is a lower bound to the bitrate below which they cannot go if the content is to be considered HD. ABR algorithms, forced to maintain HD bitrates over wireless links with constrained bandwidth, experience significant numbers of stalling events. High numbers of stalling events, particularly towards the end of a video, have a serious negative impact on enduser QoE.This paper proposes Adaptive Interface Selection (AIS) to address this issue. AIS leverages the multihomed nature of modern mobile devices and the segmented nature of video content prepared for DASHenabled clients to overcome the bandwidth constraints that hobble ABR algorithms. AIS uses multiple wireless interfaces in parallel to download content to maintain the playout buffer level to prevent stalling events. By minimizing the number of stalling events and streaming at HD compatible bitrates enduser QoE is maintained. Downloading as little content as possible over mobile networks helps protect the enduserxe2x80x99s mobile datacap.