We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

The measurement of meaning

The Transmission Control Protocol.

User-perceived quality-of-experience (QoE) is critical in Internet video applications as it impacts revenues for content providers and delivery systems. Given that there is little support in the network for optimizing such measures, bottlenecks could occur anywhere in the delivery system. Consequently, a robust bitrate adaptation algorithm in client-side players is critical to ensure good user experience. Previous studies have shown key limitations of state-of-art commercial solutions and proposed a range of heuristic fixes. Despite the emergence of several proposals, there is still a distinct lack of consensus on: (1) How best to design this client-side bitrate adaptation logic (e.g., use rate estimates vs. buffer occupancy); (2) How well specific classes of approaches will perform under diverse operating regimes (e.g., high throughput variability); or (3) How do they actually balance different QoE objectives (e.g., startup delay vs. rebuffering). To this end, this paper makes three key technical contributions. First, to bring some rigor to this space, we develop a principled control-theoretic model to reason about a broad spectrum of strategies. Second, we propose a novel model predictive control algorithm that can optimally combine throughput and buffer occupancy information to outperform traditional approaches. Third, we present a practical implementation in a reference video player to validate our approach using realistic trace-driven emulations.

/pdf/a-control-theoretic-approach-for-dynamic-adaptive-video-1mmix9lrz0.pdf

A Control-Theoretic Approach for Dynamic Adaptive Video Streaming over HTTP

Changing network conditions pose severe problems to video streaming in the Internet. HTTP adaptive streaming (HAS) is a technology employed by numerous video services that relieves these issues by adapting the video to the current network conditions. It enables service providers to improve resource utilization and Quality of Experience (QoE) by incorporating information from different layers in order to deliver and adapt a video in its best possible quality. Thereby, it allows taking into account end user device capabilities, available video quality levels, current network conditions, and current server load. For end users, the major benefits of HAS compared to classical HTTP video streaming are reduced interruptions of the video playback and higher bandwidth utilization, which both generally result in a higher QoE. Adaptation is possible by changing the frame rate, resolution, or quantization of the video, which can be done with various adaptation strategies and related client- and server-side actions. The technical development of HAS, existing open standardized solutions, but also proprietary solutions are reviewed in this paper as fundamental to derive the QoE influence factors that emerge as a result of adaptation. The main contribution is a comprehensive survey of QoE related works from human computer interaction and networking domains, which are structured according to the QoE impact of video adaptation. To be more precise, subjective studies that cover QoE aspects of adaptation dimensions and strategies are revisited. As a result, QoE influence factors of HAS and corresponding QoE models are identified, but also open issues and conflicting results are discussed. Furthermore, technical influence factors, which are often ignored in the context of HAS, affect perceptual QoE influence factors and are consequently analyzed. This survey gives the reader an overview of the current state of the art and recent developments. At the same time, it targets networking researchers who develop new solutions for HTTP video streaming or assess video streaming from a user centric point of view. Therefore, this paper is a major step toward truly improving HAS.

A Survey on Quality of Experience of HTTP Adaptive Streaming

Inter-Destination Multimedia Synchronization (IDMS) pushes social interactions to a new level. IDMS allows the users to experience multimedia together with friends, colleagues, or the family while having a real-time communication at the same time. The actual challenge of synchronizing the playout of each participant to a reference playout time is a tough task in terms of Quality of Experience (QoE). A possible solution for carrying out the synchronization is Adaptive Media Playout (AMP) where the playout speed of the multimedia is increased or decreased. In this paper we evaluate the impact of the playout variations on the QoE by adopting a crowdsourcing approach. In particular, we investigate the impact of randomly selecting content sections for adapting the playout rate compared to our approach that exploits audio-visual features of the content in order to minimize the impact on the QoE.

/pdf/a-subjective-evaluation-using-crowdsourcing-of-adaptive-3noe190jb1.pdf

A subjective evaluation using crowdsourcing of Adaptive Media Playout utilizing audio-visual content features

Dynamic and Distributed Multimedia Content Adaptation based on the MPEG-21 Multimedia Framework*

The aim of this paper is to describe a Quality of Service (QoS) model enabling to measure the perceptual quality of video transmissions by exploiting metrics from different layers (service, application, network) in an interoperable way. As such we are able to keep the quality experienced by the end user at a satisfactory level without cost-intensive subjective tests. Therefore, we propose a detailed QoS model for video transmission following the philosophy of the ITU-T's E-model for audio and show how this can be translated into interoperable description formats offered by the MPEG-21 Multimedia Framework.

Measuring quality of experience for MPEG-21-based cross-layer multimedia content adaptation

Real-time entertainment application such as the streaming of audio and video is responsible for the majority of today's Internet traffic. The transport thereof is accomplished over the top of the existing infrastructure and with MPEG-DASH interoperability is achieved. However, standards like MPEG-DASH only provide the format definition and the actual behavior of the corresponding implementations is left open for (industry) competition. In this demo paper we present our cloud encoding service and HTML5 adaptive streaming player enabling highest quality (i.e., no stalls and maximum media quality under the given conditions) and low start-up delay (for both live and on demand) at low (networking) costs. The demo comprises a feature-rich set of DASH-based application scenarios including much faster than real-time encoding/transcoding in the public cloud, live (device-to-device) streaming, support for digital rights management and advertisements, ultra high-definition and high frame rates, virtual reality, and 360° videos.

Transcoding and streaming-as-a-service for improved video quality on the web

Due to the growing demand for video streaming services, providers have to deal with increasing resource requirements for increasingly heterogeneous environments. To mitigate this problem, many works have been proposed which aim to ( ${i}$ ) improve cloud/edge caching efficiency, ( ii ) use computation power available in the cloud/edge for on-the-fly transcoding, and ( iii ) optimize the trade-off among various cost parameters, e.g. , storage, computation, and bandwidth. In this paper, we propose LwTE , a novel ${L}$ ight- ${w}$ eight ${T}$ ranscoding approach at the ${E}$ dge, in the context of HTTP Adaptive Streaming (HAS). During the encoding process of a video segment at the origin side, computationally intense search processes are going on. The main idea of LwTE is to store the optimal results of these search processes as metadata for each video bitrate and reuse them at the edge servers to reduce the required time and computational resources for on-the-fly transcoding. LwTE enables us to store only the highest bitrate plus corresponding metadata (of very small size) for unpopular video segments/bitrates. In this way, in addition to the significant reduction in bandwidth and storage consumption, the required time for on-the-fly transcoding of a requested segment is remarkably decreased by utilizing its corresponding metadata; unnecessary search processes are avoided. Popular video segments/bitrates are being stored. We investigate our approach for Video-on-Demand (VoD) streaming services by optimizing storage and computation (transcoding) costs at the edge servers and then compare it to conventional methods (store all bitrates, partial transcoding). The results indicate that our approach reduces the transcoding time by at least 80% and decreases the aforementioned costs by 12% to 70% compared to the state-of-the-art approaches.

/pdf/lwte-light-weight-transcoding-at-the-edge-144q01zgkt.pdf

Christian Timmerer

Papers

A subjective evaluation using crowdsourcing of Adaptive Media Playout utilizing audio-visual content features

Dynamic and Distributed Multimedia Content Adaptation based on the MPEG-21 Multimedia Framework*

Measuring quality of experience for MPEG-21-based cross-layer multimedia content adaptation

Transcoding and streaming-as-a-service for improved video quality on the web

LwTE: Light-Weight Transcoding at the Edge