Modeling And Dynamic Resource Allocation For High Definition And Mobile Video Streams

Video streaming traffic has been surging in the last few years, which has resulted in an increase of its Internet traffic share on a daily basis. The importance of video streaming management has been emphasized with the advent of High Definition: HD) video streaming, as it requires by its nature more network resources. In this dissertation, we provide a better support for managing HD video traffic over both wireless and wired networks through several contributions. We present a simple, general and accurate video source model: Simplified Seasonal ARIMA Model: SAM). SAM is capable of capturing the statistical characteristics of video traces with less than 5% difference from their calculated optimal models. SAM is shown to be capable of modeling video traces encoded with MPEG-4 Part2, MPEG-4 Part10, and Scalable Video Codec: SVC) standards, using various encoding settings. We also provide a large and publicly-available collection of HD video traces along with their analyses results. These analyses include a full statistical analysis of HD videos, in addition to modeling, factor and cluster analyses. These results show that by using SAM, we can achieve up to 50% improvement in video traffic prediction accuracy. In addition, we developed several video tools, including an HD video traffic generator based on our model. Finally, to improve HD video streaming resource management, we present a SAM-based delay-guaranteed dynamic resource allocation: DRA) scheme that can provide up to 32.4% improvement in bandwidth utilization

Quality of experience-centric management of adaptive video streaming services : status and challenges

Video streaming applications currently dominate Internet traffic. Particularly, HTTP Adaptive Streaming ( HAS) has emerged as the dominant standard for streaming videos over the best-effort Internet, thanks to its capability of matching the video quality to the available network resources. In HAS, the video client is equipped with a heuristic that dynamically decides the most suitable quality to stream the content, based on information such as the perceived network bandwidth or the video player buffer status. The goal of this heuristic is to optimize the quality as perceived by the user, the so-called Quality of Experience (QoE). Despite the many advantages brought by the adaptive streaming principle, optimizing users' QoE is far from trivial. Current heuristics are still suboptimal when sudden bandwidth drops occur, especially in wireless environments, thus leading to freezes in the video playout, the main factor influencing users' QoE. This issue is aggravated in case of live events, where the player buffer has to be kept as small as possible in order to reduce the playout delay between the user and the live signal. In light of the above, in recent years, several works have been proposed with the aim of extending the classical purely client-based structure of adaptive video streaming, in order to fully optimize users' QoE. In this article, a survey is presented of research works on this topic together with a classification based on where the optimization takes place. This classification goes beyond client-based heuristics to investigate the usage of server-and network-assisted architectures and of new application and transport layer protocols. In addition, we outline the major challenges currently arising in the field of multimedia delivery, which are going to be of extreme relevance in future years

Development of a Quality of Service Framework for Multimedia Streaming Applications

By the year 2012, it is expected that the majority of all Internet traffic will be video content. Coupled with this is the increasing availability of Wireless Local Area Networks (WLANs) due to their ease of deployment, flexibility and reducing roll out costs. Unfortunately the contention based access mechanism utilised by IEEE 802.11 WLANs does not suit the non-uniform or bursty bandwidth profile of a video stream which can lead to a reduced quality of service (QoS) being experienced by the end-user. In 2005, the IEEE 802.11e protocol was ratified in an attempt to solve this emerging problem. It provides for an access prioritization mechanism based upon four separate traffic classes or access categories (ACs). Each AC is characterised by a set of access parameters that determine its level of access priority which is turn determines the amount of bandwidth available to it. Computer simulation studies have shown that AC prioritisation can yield significant improvements in the QoS delivered over a WLAN. However, these studies have been based upon the use of static access parameters for the ACs. In practice, this is not a viable solution owing to the dynamic and unpredictable nature of the operating conditions on WLANs. In this thesis, an experimental study of AC prioritisation based upon adaptive tuning of the access parameters is presented. This new approach to bandwidth provisioning for video streaming is shown to yield significant improvements in the QoS under a wide range of different operating conditions. For example, it is shown that by adaptively tuning the access control parameters in response to the network conditions, the number of video frames delivered that satisfy QoS requirements is more than doubled

Performance analysis and application development of hybrid WiMAX-WiFi IP video surveillance systems

Traditional Closed Circuit Television (CCTV) analogue cameras installed in buildings and other areas of security interest necessitates the use of cable lines. However, analogue systems are limited by distance; and storing analogue data requires huge space or bandwidth. Wired systems are also prone to vandalism, they cannot be installed in a hostile terrain and in heritage sites, where cabling would distort original design. Currently, there is a paradigm shift towards wireless solutions (WiMAX, Wi-Fi, 3G, 4G) to complement and in some cases replace the wired system. A wireless solution of the Fourth-Generation Surveillance System (4GSS) has been proposed in this thesis. It is a hybrid WiMAX-WiFi video surveillance system. The performance analysis of the hybrid WiMAX-WiFi is compared with the conventional WiMAX surveillance models. The video surveillance models and the algorithm that exploit the advantages of both WiMAX and Wi-Fi for scenarios of fixed and mobile wireless cameras have been proposed, simulated and compared with the mathematical/analytical models. The hybrid WiMAX-WiFi video surveillance model has been extended to include a Wireless Mesh configuration on the Wi-Fi part, to improve the scalability and reliability. A performance analysis for hybrid WiMAX-WiFi system with an appropriate Mobility model has been considered for the case of mobile cameras. A security software application for mobile smartphones that sends surveillance images to either local or remote servers has been developed. The developed software has been tested, evaluated and deployed in low bandwidth Wi-Fi wireless network environments. WiMAX is a wireless metropolitan access network technology that provides broadband services to the connected customers. Major modules and units of WiMAX include the Customer Provided Equipment (CPE), the Access Service Network (ASN) which consist one or more Base Stations (BS) and the Connectivity Service Network (CSN). Various interfaces exist between each unit and module. WiMAX is based on the IEEE 802.16 family of standards. Wi-Fi, on the other hand, is a wireless access network operating in the local area network; and it is based on the IEEE 802.11 standards

Demonstrating Immersive Media Delivery on 5G Broadcast and Multicast Testing Networks

This work presents eight demonstrators and one showcase developed within the 5G-Xcast project. They experimentally demonstrate and validate key technical enablers for the future of media delivery, associated with multicast and broadcast communication capabilities in 5th Generation (5G). In 5G-Xcast, three existing testbeds: IRT in Munich (Germany), 5GIC in Surrey (UK), and TUAS in Turku (Finland), have been developed into 5G broadcast and multicast testing networks, which enables us to demonstrate our vision of a converged 5G infrastructure with fixed and mobile accesses and terrestrial broadcast, delivering immersive audio-visual media content. Built upon the improved testing networks, the demonstrators and showcase developed in 5G-Xcast show the impact of the technology developed in the project. Our demonstrations predominantly cover use cases belonging to two verticals: Media & Entertainment and Public Warning, which are future 5G scenarios relevant to multicast and broadcast delivery. In this paper, we present the development of these demonstrators, the showcase, and the testbeds. We also provide key findings from the experiments and demonstrations, which not only validate the technical solutions developed in the project, but also illustrate the potential technical impact of these solutions for broadcasters, content providers, operators, and other industries interested in the future immersive media delivery.Comment: 16 pages, 22 figures, IEEE Trans. Broadcastin