Abstract: In this tutorial we present state of the art and challenges ahead in over-the-top content delivery. It particular, the goal of this tutorial is to provide an overview of adaptive media delivery, specifically in the context of HTTP adaptive streaming (HAS) including the recently ratified MPEG-DASH standard. The main focus of the tutorial will be on the common problems in HAS deployments such as client design, QoE optimization, multi-screen and hybrid delivery scenarios, and synchronization issues. For each problem, we will examine proposed solutions along with their pros and cons. In the last part of the tutorial, we will look into the open issues and review the work-in-progress and future research directions.

Abstract: Social networks have become pervasive and have changed the way of social interaction. The traditional TV experience drifts from an event tied to a certain place with the family or friends to a location-independent and distributed social experience. Additionally, more and more video on-demand services adopt a pull-based streaming approach. In order to provide a synchronized and distributed TV experience we introduce a self-organized Inter-Destination Multimedia Synchronization (IDMS) framework for adaptive media streaming. In particular, we extend the principles of IDMS to adaptive media streaming over HTTP (i.e., MPEG-DASH) and enable a synchronized multimedia playback among geographically distributed clients. Therefore, we introduce session management to MPEG-DASH and for negotiating on a reference playback timestamp among the participating peers in an IDMS session we propose a distributed control scheme. We evaluate our proposed scheme with respect to scalability and time required for negotiating on the reference playback timestamp. Furthermore, we investigate how to compensate the identified asynchronism by using adaptive media playout with respect to the Quality of Experience (QoE). Therefore, we define a temporal distortion measure for audio and video which allows us to model the impact of playback rate variations on the QoE. This measure is evaluated by conducting a subjective quality assessment using crowdsourcing.

Abstract: The MPEG-DASH standard allows the client-centric access to different representations of video content via the HTTP protocol. The client can flexibly switch between different qualities, i.e., different bit rates and thus avoid waiting times during the video playback due to empty playback buffers. However, quality switches and the playback of lower qualities is perceived by the user which may reduce the Quality of Experience (QoE). Therefore, novel algorithms are required which manage the streaming behavior with respect to the user's requirements and which do not waste network resources. As indicated by recent studies, scalable video coding (SVC) may use the current network and content distribution infrastructure in a more efficient way than with single layer codecs. The contribution of this paper is the design and the implementation of a novel DASH/SVC streaming algorithm. By means of measurements in a test-bed, its performance and benefits are evaluated and compared to existing algorithms from an user-centric view point with objective performance metrics. Our findings show that the proposed algorithm outperforms other DASH mechanisms in terms of video quality, low switching frequency and usage of the available resources in a realistic mobile network scenario. This is a first step towards true QoE management of video streaming in the Internet with DASH and SVC.

Abstract: Scalability within media coding allows for content adaptation towards heterogeneous user contexts and enables in-network adaptation. However, there is no straightforward solution how to encode the content in a scalable way while maximizing rate-distortion performance. In this paper we provide encoding guidelines for scalable video coding based on a survey of media streaming industry solutions and a comprehensive performance evaluation using four state of the art scalable video codecs with a focus on high-definition content (1080p).