Abstract: In this paper, we present our implementation and evaluation of Dynamic Adaptive Streaming over Content centric networking (DASC) which implements MPEG Dynamic Adaptive Streaming over HTTP (DASH) utilizing a Content Centric Networking (CCN) naming scheme to identify content segments in a CCN network. In particular, video segments formatted according to MPEG-DASH are available in different quality levels but instead of HTTP, CCN is used for referencing and delivery. Based on the conditions of the network, the DASC client issues interests for segments achieving the best throughput. Due to segment caching within the network, subsequent requests for the same content can be served quicker. As a result, the quality of the video a user receives progressively improves, effectively overcoming bottlenecks in the network. We present two sets of experiments to evaluate the performance of DASC showing that throughput indeed improves. However, the generated overhead is relatively large and the adaptation strategy used for DASH that assumes an end-to-end connection could be revised for the hop-by-hop architecture of CCN.

Abstract: This paper presents the usage of CCN, which is a candidate for the next-generation Internet, in combination with the new Dynamic Adaptive Streaming over HTTP (DASH) standard, which was recently ratified by ISO/IEC MPEG. In contrast to the Internet Protocol, which is mainly based on the host-to-host connection paradigm originated in the 1970s, Content Centric Networking (CCN) focuses on the content itself, instead of its location. Considering the dominance of multimedia traffic in todays' Internet, the streaming performance of DASH over CCN as well as the problems introduced by this combination is worth to be investigated in detail. Therefore, we evaluate the protocol overhead introduced by the usage of CCN compared to the HTTP versions 1.0 and 1.1. Furthermore, the performance of DASH over CCN under different network conditions is compared to the performance of HTTP 1.0/1.1. Our results showed that although CCN comes together with higher protocol overhead than HTTP 1.0/1.1 as well as a prototype implementation, it can definitely compete with HTTP 1.0 in media streaming. Based on the evaluation results, problems as well as improvement possibilities are identified, which are the basis for future work in this area.

Abstract: This paper presents the usage of Content Centric Networking (CCN) for adaptive multimedia streaming in mobile environments, leveraging the recent ISO/IEC MPEG Dynamic Adaptive Streaming over HTTP (DASH) standard. The performance of DASH over CCN is evaluated using real-world mobile bandwidth traces and compared to previous evaluations of different DASH-based as well as proprietary systems. As there are no client-server connections in CCN, it offers the possibility to transfer data from multiple sources as well as over multiple links in parallel, which is definitely an important feature, e.g., for mobile devices offering multiple network links. This functionality is used and evaluated in this paper in combination with DASH, making it possible to dynamically choose the best performing link for media streaming, which is a clear advantage over DASH using HTTP and the TCP/IP protocol stack. The evaluation therefore investigates DASH over CCN in two scenarios using synthetic and real-world mobile bandwidth traces respectively, showing a significantly better performance than conventional DASH using only one connection.

Abstract: The delivery of multimedia content over HTTP and on top of existing Internet infrastructures is becoming the preferred method within heterogeneous environment. The basic design principle is having an intelligent client which selects given and applicable media representations by issuing HTTP requests for individual segments based on the users' context and current conditions. Typically, this client behavior differs between implementations of the same kind and for the objective evaluations thereof appropriate datasets are needed. This paper presents a distributed dataset for the recently published MPEG-DASH standard which is mirrored at different sites across Europe, namely Klagenfurt, Paris, and Prague. A client implementation may choose to request segments from these sites and dynamically switch to a different location, e.g., in case the one currently used causes any issues. Thus, this distributed DASH dataset can be used for real-world evaluations enabling the simulation of switching between different content delivery networks.

Abstract: MPEG-M is a suite of ISO/IEC standards (ISO/IEC 23006) that has been developed under the auspices of Moving Picture Experts Group (MPEG). MPEG-M, also known as Multimedia Service Platform Technologies (MSPT), facilitates a collection of multimedia middleware APIs and elementary services as well as service aggregation so that service providers can offer users a plethora of innovative services by extending current IPTV technology toward the seamless integration of personal content creation and distribution, e-commerce, social networks and Internet distribution of digital media.

Abstract: Scalable Video Coding (SVC) in media streaming enables dynamic adaptation based on device capabilities and network conditions. In this paper, we investigate deployment options of SVC for Dynamic Adaptive Streaming over HTTP (DASH) with a special focus on scalability options, which are relevant for dynamic adaptation, especially in wireless and mobile environments. We evaluate the performance of SVC with respect to spatial and quality scalability options and compare it to non-scalable Advanced Video Coding (AVC). Performance evaluations are performed for various encoder implementations with high-definition (1080p) content. We show that a hybrid approach with multiple independent SVC bitstreams can have advantages in storage requirements at comparable rate-distortion performance.

Abstract: On TV screens, PCs, tablets, and mobile phones, video streaming has become a constant companion in our daily lives. For every video, we expect high visual quality, free from distortions, that is adjusted to the device at hand. But how can streaming systems cope with the increasing network traffic, the subsequent network congestions, and the different characteristics of end-user terminals? This thesis covers approaches for distributed adaptation of scalable video resources in media delivery. Scalable video resources consist of several layers that enable various spatial resolutions, frame rates, or qualities of a content. By dropping some of these layers, the video can be adjusted to the available bandwidth or to a specific end-user terminal. The adaptation can be performed on the sender side, on the receiver side, and on one or more network nodes. Scalable media coding can also help to reduce bandwidth requirements in multicast scenarios (e.g., for IPTV). One popular realization of scalable media coding is the Scalable Video Coding (SVC) standard. This thesis consists of three main parts, addressing various challenges towards efficient SVC adaptation. The first part of this thesis focuses on the encoding of SVC. In order to enable efficient adaptation, the configuration of layers has to be carefully chosen at encoding time. Thus, the performances of various encoding configurations and encoder implementations are evaluated. Furthermore, encoding guidelines for SVC are developed, which are aligned with recommendations of industry streaming solutions. The evaluation results of the developed SVC encoding guidelines suggest that quality scalability should be preferred over spatial scalability for adaptive streaming scenarios. Different resolutions for supporting device classes should rather be provided as separate SVC streams. The second part of this thesis deals with the fact that scalable media formats, such as SVC, are still not widely adopted neither on the sender side nor on the end-user terminal. In order to enable the deployment of SVC for network transmission and to improve the support for streaming to heterogeneous devices, the concept of SVC tunneling is introduced in this thesis. The video is transcoded to SVC at the sender side and then transcoded back to another video format at the receiver side at an advanced home-gateway. However, the transcoding between video formats has a negative impact on the video quality. The trade-off between quality loss and bandwidth efficiency of SVC tunneling is evaluated. SVC tunneling with quality layers enables bandwidth savings at moderate quality loss (approx. 2.5 dB) compared to streaming separate non-scalable representations of the same qualities. In the third part of this thesis, adaptation techniques for content-aware networks are investigated. In content-aware networks, some network nodes are capable to dynamically adapt video streams in reaction to varying network loads. With the increasing adoption of HTTP streaming, adaptation at the client side becomes a main factor for the viewing experience. The switch between two representations (e.g., different bitrates) of a video can disrupt that viewing experience. To reduce the effect of an abrupt quality change, the approach of a smooth transition between representations is developed and evaluated. A subjective user study indicates that this approach can indeed improve the overall viewing quality. Finally, the findings of the previous parts are integrated in an adaptive end-to-end SVC streaming system. Evaluations of this streaming system show that the developed adaptation framework significantly improves the video quality under packet loss (by up to 6 dB) compared to non-adaptive streaming.

Abstract: When an adaptive media streaming system has to switch from one representation of the content to another, the switch causes viewer distraction. We introduce the concept of representation switch smoothing for alleviating the distraction and improving the overall quality of experience. As adaptive HTTP streaming systems typically deploy video buffers on the client side, the adaptation decision is known far enough ahead of playout time to perform a seamless transition between quality representations. We discuss implementation considerations for an adaptive HTTP streaming system with scalable video coding, present a subjective evaluation of the proposed approach, and identify factors that influence how smooth transitions are perceived.

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).

Abstract: Scalable Video Coding (SVC) in media streaming enables dynamic adaptation based on device capabilities and network conditions. In this paper, we investigate deployment options of SVC for Dynamic Adaptive Streaming over HTTP (DASH) with a special focus on scalability options, which are relevant for dynamic adaptation, especially in wireless and mobile environments. We establish encoding recommendations and evaluate the performance of SVC with respect to spatial and quality scalability options and compare it to non-scalable Advanced Video Coding (AVC). Performance evaluations are performed for various encoder implementations with high-definition (1080p) content. We show that a hybrid approach with multiple independent SVC bitstreams can have advantages in storage requirements at comparable rate-distortion performance.

Abstract: Given that multimedia services are becoming increasingly popular, they are expected to play a dominant role for the Future Internet. In this context, it is essential that Content-Aware Networking (CAN) architectures, as envisaged in the frame of the Future Internet, explicitly address the efficient delivery and processing of multimedia content. This article proposes adopting a content-aware approach into the network infrastructure, thus making it capable of identifying, processing, and manipulating (i.e., adapting, caching, etc.) media streams and objects in real time towards Quality of Service/Experience (QoS/QoE) maximization. Our proposal is built upon the exploitation of scalable media coding technologies within such a content-aware networking environment and is discussed based on four representative use cases for media delivery (unicast, multicast, peer-to-peer, and adaptive HTTP streaming) and with respect to a selection of CAN challenges, specifically flow processing, caching/buffering, and QoS/QoE management.

Abstract: Multimedia (especially video) services constitute a dominant and ever increasing portion of the global Internet traffic, while they are expected to also play a major role in the Future Internet scene. In order to address this reality in the networking domain, a promising perspective is to gradually shift from the current, service-unaware, best-effort nature of IP networks into a network logic which is service-aware – and, in specific, media-aware. This chapter discusses how media-awareness can be introduced in the networking domain in a way which is both feasible and scalable, leveraging at the same time state-of-the-art technologies in video representations, such as Scalable Video Coding (SVC) and Dynamic Adaptive Streaming over HTTP (DASH).

Abstract: We present an improved version of last year’s winner of the Video Browser Showdown. In a preprocessing step video segments are detected and clustered in several latent classes of similar content based on color and motion information. The navigation bars of our video browser are then augmented with different colors indicating where elements of the detected clusters are located. As humans are able to classify the content of clusters fast, they can benefit from this information when browsing through a video.

Abstract: While accuracy and speed get a lot of attention in video retrieval research, the investigation of interactive retrieval tools gets less attention and is often regarded as trivial. We want to show that even simple ideas have potential to improve the retrieval performance by giving some automated support to the browsing user. We present a video browsing concept where video segments are clustered in several latent classes of similar content. The navigation bars of our video browser are augmented with different colors indicating where elements of these clusters are located. As humans are able to classify the content of clusters fast, they can benefit from this information when browsing a video. We present a study where we investigated how humans can be supported in different video browsing tasks with a color-based and a motion-based clustering of video content.

Abstract: This paper shows how adaptive streaming and on-device caching can be used to provide an always available video service. A DASH client has been extended to deal with periods of zero network connectivity, and seamlessly works in conjunction with CCN to provide local storage that is intelligently updated to provide an improved quality of experience.

Abstract: The Video Browser Showdown (VBS) is a live competition for evaluating video browsing tools regarding their efficiency at known-item search (KIS) tasks. The first VBS was held at MMM 2012 with eight teams working on 14 tasks, of which eight were completed by expert users and six by novices. We describe the details of the competition, analyze results regarding the performance of tools, the differences between the tasks and the nature of the false submissions.

Abstract: Dynamic Adaptive Streaming over HTTP (DASH) is referred to as a multimedia streaming standard to deliver high quality multimedia content over the Internet using conventional HTTP Web servers. As a fundamental feature, it enables automatic switching of quality levels according to network conditions, user requirements, and expectations. Currently, the proposed adaptation schemes for HTTP streaming mostly rely on throughput measurements and/or buffer-related metrics, such as buffer exhaustion and levels. In this paper, we propose to enhance the DASH adaptation logic by feeding it with additional information from our evaluation of the users' perception approximating the user- perceived quality of video playback. The proposed model aims at conveniently combining TCP-, buffer-, and media content-related metrics as well as user requirements and expectations to be used as an input for the DASH adaptation logic. Experiments have demonstrated that the chosen model enhances the capability of the adaptation logic to select the optimal video quality level. Finally, we integrated all our findings into a real DASH system with QoE monitoring capabilities.

Abstract: Why do people record videos and share them? While the question seems to be simple, user intentions have not yet been investigated for video production and sharing. A general taxonomy would lead to adapted information systems and multimedia interfaces tailored to the users' intentions. We contribute (1) an exploratory user study with 20 participants, examining the various facets of user intentions for video production and sharing in detail and (2) a novel set of user intention clusters for video production, grounded empirically in our study results. We further reflect existing work in specialized domains (i.e. video blogging and mobile phone cameras) and show that prevailing models used in other multimedia fields (e.g. photography) cannot be used as-is to reason about video recording and sharing intentions.

Abstract: A novel visual multimedia content encryption method based on cellular automata (CA) is presented in this paper. The proposed algorithm is based on an attribute of the eXclusive-OR (XOR) logic gate, according to which, its application to a square-sized CA has the ability to reconstruct the original content of a CA after a preset number of iterations. The resulted encrypted image is a lossless representation of the original/plaintext image, i.e. there is no loss of either resolution or contrast. Experimental results indicate that the encrypted image does not contain any statistical information able to reveal the original image.