Thomas Zinner

A Survey on Quality of Experience of HTTP Adaptive Streaming

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.

Quantification of YouTube QoE via Crowdsourcing

This paper addresses the challenge of assessing and modeling Quality of Experience (QoE) for online video services that are based on TCP-streaming. We present a dedicated QoE model for You Tube that takes into account the key influence factors (such as stalling events caused by network bottlenecks) that shape quality perception of this service. As second contribution, we propose a generic subjective QoE assessment methodology for multimedia applications (like online video) that is based on crowd sourcing - a highly cost-efficient, fast and flexible way of conducting user experiments. We demonstrate how our approach successfully leverages the inherent strengths of crowd sourcing while addressing critical aspects such as the reliability of the experimental data obtained. Our results suggest that, crowd sourcing is a highly effective QoE assessment method not only for online video, but also for a wide range of other current and future Internet applications.

Heuristic Approaches to the Controller Placement Problem in Large Scale SDN Networks

Software Defined Networking (SDN) marks a paradigm shift towards an externalized and logically centralized network control plane. A particularly important task in SDN architectures is that of controller placement, i.e., the positioning of a limited number of resources within a network to meet various requirements. These requirements range from latency constraints to failure tolerance and load balancing. In most scenarios, at least some of these objectives are competing, thus no single best placement is available and decision makers need to find a balanced trade-off. This work presents POCO, a framework for Pareto-based Optimal COntroller placement that provides operators with Pareto optimal placements with respect to different performance metrics. In its default configuration, POCO performs an exhaustive evaluation of all possible placements. While this is practically feasible for small and medium sized networks, realistic time and resource constraints call for an alternative in the context of large scale networks or dynamic networks whose properties change over time. For these scenarios, the POCO toolset is extended by a heuristic approach that is less accurate, but yields faster computation times. An evaluation of this heuristic is performed on a collection of real world network topologies from the Internet Topology Zoo. Utilizing a measure for quantifying the error introduced by the heuristic approach allows an analysis of the resulting trade-off between time and accuracy. Additionally, the proposed methods can be extended to solve similar virtual functions placement problems which appear in the context of Network Functions Virtualization (NFV).

Interfaces, attributes, and use cases: A compass for SDN

The term Software Defined Networking (SDN) is prevalent in todays discussion about future communication networks. As with any new term or paradigm, however, no consistent definition regarding this technology has formed. The fragmented view on SDN results in legacy products being passed off by equipment vendors as SDN, academics mixing up the attributes of SDN with those of network virtualization, and users not fully understanding the benefits. Therefore, establishing SDN as a widely adopted technology beyond laboratories and insular deployments requires a compass to navigate the multitude of ideas and concepts that make up SDN today. The contribution of this article represents an important step toward such an instrument. It gives a thorough definition of SDN and its interfaces as well as a list of its key attributes. Furthermore, a mapping of interfaces and attributes to SDN use cases is provided, highlighting the relevance of the interfaces and attributes for each scenario. This compass gives guidance to a potential adopter of SDN on whether SDN is in fact the right technology for a specific use case.

SDN-Based Application-Aware Networking on the Example of YouTube Video Streaming

Application-Aware Networking is a promising approach to provide good application quality to users in scenarios with limited network resources, like todays access networks. With SDN, a particularly interesting method to enable flowbased traffic management in networks has become available. In this work we take a look at how a specific application, i.e., YouTube Streaming, can benefit from such an SDN-based Application-Aware Network. We implement and investigate an approach based on Deep Packet Inspection (DPI) and one based on direct information input from the application in an OpenFlow testbed in order to show, how these different types of application information can be exploited to enhance the Quality of Experience (QoE). Furthermore, we determine the overhead caused by each of the presented approaches.

Impact of frame rate and resolution on objective QoE metrics

Video streaming applications are a major driver for the evolution of the future Internet. In this paper we introduce a framework for QoE management for video streaming systems based on the H.264/SVC codec, the scalable extension of H.264/AVC. A relevant feature is to control the user perceived quality of experience (QoE) by exploiting parameters offered by SVC. A proper design of a control mechanism requires the quantification of the main influence parameters on the QoE. For this purpose, we conducted a measurement study and quantified the influence of i) video resolution, ii) scaling method, iii) video frame rate and iv) video content types on the QoE by means of the SSIM and VQM full-reference metrics. Further, we discuss the trade-off between these different control knobs and their influence on the QoE.

Pareto-optimal resilient controller placement in SDN-based core networks

Recently, Software Defined Networking (SDN) has gained a lot of attention, even for the use in core communication networks. When deploying SDN in large core networks, the number and location of controllers must be carefully planned. A first study on this topic by Heller et al. [3] was followed by more detailed publications that included resilience or dynamic controller provisioning. In our previous work [2], we provide an overview over related work and include different resilience issues in the controller placement process. We argued that it is not sufficient to look only at node-to-controller latencies but a controller placement should also fulfill certain resilience constraints especially for the control plane.

Assessing effect sizes of influence factors towards a QoE model for HTTP adaptive streaming

HTTP Adaptive Streaming (HAS) is employed by more and more video streaming services in the Internet. It allows to adapt the downloaded video quality to the current network conditions, and thus, avoids stalling (i.e., playback interruptions) to the greatest possible extend. The adaptation of video streams is done by switching between different quality representation levels, which influences the user perceived quality of the video stream. In this work, the influence of several adaptation parameters, namely, switch amplitude (i.e., quality level difference), switching frequency, and recency effects, on Quality of Experience (QoE) is investigated. Therefore, crowdsourcing experiments were conducted in order to collect subjective ratings for different adaptation-related test conditions. The results of these subjective studies indicate the influence of the adaptation parameters, and based on these findings a simplified QoE model for HAS is presented, which only relies on the switch amplitude and the playback time of each layer.

Future Internet research and experimentation

The German Lab (G-Lab) project aims to investigate architectural concepts and technologies for a new inter-networking architecture as an integrated approach between theoretic and experimental studies. Thus G-Lab consists of two major fields of activities: research studies of future network components and the design and setup of experimental facilities. Both are controlled by the same community to ensure that the experimental facility meets the demands of the researchers. Researchers gain access to virtualized resources or may gain exclusive access to resources if necessary. We present the current setup of the experimental facility, describing the available hardware, management of the platform, the utilization of the PlanetLab software and the user management. Moreover, a new approach to setup and deploy virtual network topologies will be described.

On the impact of quality adaptation in SVC-based P2P video-on-demand systems

P2P Video-on-Demand (VoD) based on Scalable Video Coding (SVC) (the scalable extension of the H.264/AVC standard) is gaining momentum in the research community, as it provides elegant adaptation to heterogeneous resources and network dynamics. The major question is, how do the adaptation algorithms and designs affect the overall perceived performance of the system? Better yet, how can the performance of an SVC-based VoD system be defined? This paper explores the impact and trade-offs of SVC-based quality adaptation with focus on the SVC layer selection algorithms, which are performed at different streaming stages. We carry out extensive experiments to evaluate the performance in terms of session quality (start-up delay, video stalls) and delivered SVC video quality (layer switches, received layers), and find out that these two metrics exhibit a trade-off. Our analysis and conclusions give multimedia providers insights on how to design and fine-tune their VoD system in order to achieve best performance.