Christopher Mueller

Adaptive streaming over Content Centric Networks in mobile networks using multiple links

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.

A proxy effect analyis and fair adatpation algorithm for multiple competing Dynamic Adaptive Streaming over HTTP clients

Multimedia streaming technologies based on the Hypertext Transfer Protocol (HTTP) are very popular and used by many content providers such as Netflix, Hulu, and Vudu. Recently, ISO/IEC MPEG has ratified Dynamic Adaptive Streaming over HTTP (DASH) which extends the traditional HTTP streaming with an adaptive component addressing the issue of varying bandwidth conditions that users are facing in networks based on the Internet Protocol (IP). Additionally, industry has already deployed several solutions based on such an approach which simplifies large scale deployment because the whole streaming logic is located at the client. However, these features may introduce drawbacks when multiple clients compete for a network bottleneck due to the fact that the clients are not aware of the network infrastructure such as proxies or other clients. This paper identifies these negative effects and the evaluation thereof using MPEG-DASH and Microsoft Smooth Streaming. Furthermore, we propose a novel adaptation algorithm introducing the concept of fairness regarding a cluster of clients. In anticipation of the results we can conclude that we achieve more efficient bottleneck bandwidth utilization and less quality switches.

Adaptive multimedia streaming in information-centric networks

ICN has received a lot of attention in recent years, and is a promising approach for the Future Internet design. As multimedia is the dominating traffic in todays and (most likely) the Future Internet, it is important to consider this type of data transmission in the context of ICN. In particular, the adaptive streaming of multimedia content is a promising approach for usage within ICN, as the client has full control over the streaming session and has the possibility to adapt the multimedia stream to its context (e.g. network conditions, device capabilities), which is compatible with the paradigms adopted by ICN. In this article we investigate the implementation of adaptive multimedia streaming within networks adopting the ICN approach. In particular, we present our approach based on the recently ratified ISO/IEC MPEG standard Dynamic Adaptive Streaming over HTTP and the ICN representative Content-Centric Networking, including baseline evaluations and open research challenges.

Towards Bandwidth Efficient Adaptive Streaming of Omnidirectional Video over HTTP: Design, Implementation, and Evaluation

Real-time entertainment services such as streaming audiovisual content deployed over the open, unmanaged Internet account now for more than 70% during peak periods. More and more such bandwidth hungry applications and services are proposed like immersive media services such as virtual reality and, specifically omnidirectional/360-degree videos. The adaptive streaming of omnidirectional video over HTTP imposes an important challenge on todays video delivery infrastructures which calls for dedicated, thoroughly designed techniques for content generation, delivery, and consumption.; AB@This paper describes the usage of tiles --- as specified within modern video codecs such HEVC/H.265 and VP9 --- enabling bandwidth efficient adaptive streaming of omnidirectional video over HTTP and we define various streaming strategies. Therefore, the parameters and characteristics of a dataset for omnidirectional video are proposed and exemplary instantiated to evaluate various aspects of such an ecosystem, namely bitrate overhead, bandwidth requirements, and quality aspects in terms of viewport PSNR. The results indicate bitrate savings from 40% (in a realistic scenario with recorded head movements from real users) up to 65% (in an ideal scenario with a centered/fixed viewport) and serve as a baseline and guidelines for advanced techniques including the outline of a research roadmap for the near future.

Demo paper: Libdash - An open source software library for the MPEG-DASH standard

Dynamic Adaptive Streaming over HTTP (DASH) is an ISO/IEC MPEG standard which enables the convenient and smooth transportation of multimedia data to heterogeneous end devices over networks with variable bandwidth conditions. This kind of streaming technology is mainly used with HTTP 1.0 and 1.1 respectively, which both have some drawbacks. Therefore, the IETF has started the development of HTTP 2.0, which is based on Googles SPDY proposal and already supported by several major companies, e.g., Facebook, Twitter, Akamai, Mozilla and obviously Google. Furthermore, Content Centric Networking (CCN) is another novel approach for future networks that is considered as an revolutionary approach compared to HTTP 2.0. The CCN communication paradigm is completely different and does not rely on direct connections between hosts, it rather focuses on the content. This paper demonstrates DASH with HTTP 2.0/SPDY and CCN using our universal libdash library. Moreover, different mechanisms of DASH will be shown that can be used to provide on-demand and live content in an efficient and comfortable way.

Oscillation compensating Dynamic Adaptive Streaming over HTTP

Streaming multimedia over the Internet is omnipresent but still in its infancy, specifically when it comes to the adaptation based on bandwidth/throughput measurements, clients competing for limited/shared bandwidth, and the presence of a caching infrastructure. In this paper we present a buffer-based adaptation logic in combination with a toolset of client metrics to compensate for erroneous adaptation decisions. These erroneous adaptation decisions are due to insufficient network information available at the client and issues introduced when multiple clients compete for limited/shared bandwidth and/or when caches are deployed. Our metrics enable the detection of oscillations on the client - in contrast to server-based approaches - and provide an effective compensation mechanism. We evaluate the proposed adaptation logic, which incorporates the oscillation detection and compensation method, and compare it against a throughput-based adaptation logic for scenarios comprising competing clients with and without caching enabled. In anticipation of the results, we show how the presented metrics detect oscillation periods and how such undesirable situations can be compensated while increasing the effective media throughput of the clients.

AdViSE: Adaptive Video Streaming Evaluation Framework for the Automated Testing of Media Players

Today we can observe a plethora of adaptive video streaming services and media players which support interoperable formats like DASH and HLS. Most of the players and their rate adaptation algorithms work as a black box. We have developed a system for easy and rapid testing of media players under various network scenarios. In this paper, we introduce AdViSE, the Adaptive Video Streaming Evaluation framework for the automated testing of adaptive media players. The presented framework is used for the comparison and testing of media players in the context of adaptive video streaming over HTTP in web/HTML5 environments.; AB@The demonstration showcases a series of experiments with different media players under given context conditions (e.g., network shaping, delivery format). We will also demonstrate the real-time capabilities of the framework and offline analysis including several QoE metrics with respect to a newly introduced bandwidth index.

An open source MPEG DASH evaluation suite

In this paper we demonstrate our MPEG-DASH evaluation suite, which comprises several components on the client side as well as on the server side. The major client components are the VLC DASH plugin, libDASH, and DASH-JS, a JavaScript-based DASH client. These tools enable performance tests on various platforms, e.g., Windows and Linux as well as mobile platforms such as Android. Moreover, due to their flexible structure it is possible to integrate adaptation logics and evaluate them under consistent conditions. On the server side we provide the content generation tool DASHEncoder, our MPEG-DASH datasets well as the MPEG-DASH conformance validator.

Investigation of YouTube regarding Content Provisioning for HTTP Adaptive Streaming

About 300 hours of video are uploaded to YouTube every minute. The main technology to delivery YouTube content to various clients is HTTP adaptive streaming and the majority of todays internet traffic comprises streaming audio and video. In this paper, we investigate content provisioning for HTTP adaptive streaming under predefined aspects representing content features and upload characteristics as well and apply it to YouTube. Additionally, we compare the YouTubes content upload and processing functions with a commercially available video encoding service. The results reveal insights into YouTubes content upload and processing functions and the methodology can be applied to similar services. All experiments conducted within the paper allow for reproducibility thanks to the usage of open source tools, publicly available datasets, and scripts used to conduct the experiments on virtual machines.