Quality of experience for HTTP adaptive streaming services

Ozgur Oyman, Sarabjot Singh
2012 IEEE Communications Magazine  
INTRODUCTION With the introduction of smartphones like the iPhone™ and Android™ based platforms, the emergence of new tablets like the iPad™, and the continued growth of netbooks, ultrabooks, and laptops, there is an explosion of powerful mobile devices in the market that are capable of displaying high-quality video content. In addition, these devices are capable of supporting various video streaming applications and interactive video applications like videoconferencing, and they can capture
more » ... eo for video sharing, video blogging, video Twitter™, and video broadcasting applications. Cisco predicts that mobile traffic will grow by a factor of 26 until 2015 (almost double every year), and that mobile traffic will be dominated by video; for example, by 2015, various forms of video will exceed 90 percent of global consumer traffic, and almost 66 percent of the world's mobile traffic will be video. 1 As a result, future wireless networks will need to be optimized for the delivery of a range of video content and video-based applications. However, video communication over mobile broadband networks today is challenging due to limitations in bandwidth and difficulties in maintaining high reliability, quality, and latency demands imposed by rich multimedia applications. Even with the migration from 3G to 4G networks -or RAN and backhaul upgrades to 3G networks -the demand on capacity for multimedia traffic will continue to increase. As subscribers take advantage of new multimedia content, applications, and devices, they will consume all available bandwidth and still expect the same quality of service that came with their original service plans -if not better. Such consumer demand requires exploration of new ways to optimize future wireless networks for video services toward delivering higher user capacity to serve more users and also deliver enhanced quality of experience (QoE) for a rich set of video applications. One of the key video-enhancing solutions is adaptive streaming, which is an increasingly promising method to deliver video to end users allowing enhancements in QoE and network bandwidth efficiency. Adaptive streaming aims to optimize and adapt the video configurations over time in order to deliver the best possible quality video to the user at any given time, considering changing link or network conditions, device capabilities, and content characteristics. Adaptive streaming is especially effective in better tackling the bandwidth limitations of wireless networks, but also it allows for more intelligent video streaming that is device-aware and content-aware. While adaptive streaming technologies support only 17 percent of the Internet video traffic today, the adaptive streaming portion of Internet video is anticipated to grow at an average of 77 percent a year toward supporting 51 percent of Internet video by 2015, according to a recent study by TDG Research. 2 ABSTRACT The growing consumer demand for mobile video services is one of the key drivers of the evolution of new wireless multimedia solutions requiring exploration of new ways to optimize future wireless networks for video services towards delivering enhanced quality of experience (QoE). One of these key video enhancing solutions is HTTP adaptive streaming (HAS), which has recently been spreading as a form of Internet video delivery and is expected to be deployed more broadly over the next few years. As a relatively new technology in comparison with traditional push-based adaptive streaming techniques, deployment of HAS presents new challenges and opportunities for content developers, service providers, network operators and device manufacturers. One of these important challenges is developing evaluation methodologies and performance metrics to accurately assess user QoE for HAS services, and effectively utilizing these metrics for service provisioning and optimizing network adaptation. In that vein, this article provides an overview of HAS concepts, and reviews the recently standardized QoE metrics and reporting framework in 3GPP. Furthermore, we present an end-to-end QoE evaluation study on HAS conducted over 3GPP LTE networks and conclude with a discussion of future challenges and opportunities in QoE optimization for HAS services. IEEE Communications Magazine • April 2012 21 Most of the expected broad adoption of adaptive streaming will be driven by new deployments over the existing web infrastructure based on HTTP [1], and this kind of streaming is referred here as HTTP adaptive streaming (HAS). HAS follows the pull-based streaming paradigm rather than the traditional push-based streaming based on stateful protocols such as the Real-Time Streaming Protocol (RTSP) [2] , where the server keeps track of client state and drives the streaming. In contrast, in pull-based streaming such as HAS, the client plays the central role by carrying the intelligence that drives the video adaptation, since HTTP is a stateless protocol. Several important factors have influenced this paradigm shift from traditional push-based streaming to HTTP streaming, including: • Broad market adoption of HTTP and TCP/IP protocols; they support the majority of the Internet services offered today. • HTTP-based delivery avoids NAT and firewall traversal issues. • A broad deployment of HTTP-based (nonadaptive) progressive download solutions already exists today, which can conveniently be upgraded to support HAS. • The ability to use standard/existing HTTP servers and caches instead of specialized streaming servers allows reuse of the existing infrastructure, thereby provides better scalability and cost effectiveness. Accordingly, the broad deployment of HAS technologies will serve as a major enhancement to (non-adaptive) progressive download methods, allowing for enhanced QoE enabled by intelligent adaptation to different link conditions, device capabilities, and content characteristics. HAS has already been spreading as a form of Internet video delivery with the recent deployments of proprietary solutions such as Apple HTTP Live Streaming, Microsoft Smooth Streaming, and Adobe HTTP Dynamic Streaming. 3 In the meantime, standardization of HAS has also made great progress with the recent completion of technical specifications by various standards bodies including the Third Generation Partnership Project (3GPP), Motion Picture Experts Group (MPEG), and Open IPTV Forum (OIPF) [3] [4] [5] [6] [7] . Going forward, future deployments of HAS are expected to converge through broad adoption of these standardized solutions referred to as dynamic adaptive streaming over HTTP (DASH). As a relatively new technology in comparison with traditional push-based adaptive streaming techniques, deployment of DASH and associated HAS techniques presents new challenges and opportunities for content developers, service providers, network operators and device manufacturers. One of these important challenges is developing evaluation methodologies and performance metrics to accurately assess user QoE for HAS services, and effectively utilizing these metrics for service provisioning and optimizing network adaptation. In that vein, this article provides an overview of HAS concepts and recent DASH standardization, and reviews the recently adopted QoE metrics and reporting framework in 3GPP standards. Furthermore, we present an end-to-end QoE evaluation study on HAS conducted over 3GPP LTE networks and conclude with a discussion of future directions and challenges in QoE optimization for HAS services.
doi:10.1109/mcom.2012.6178830 fatcat:e7fbb64qbbgqdehj4uv2wh5fm4