Video Quality Prediction for Video over Wireless Access Networks (UMTS and WLAN)

Transmission of video content over wireless access networks (in particular, Wireless Local Area Networks (WLAN) and Third Generation Universal Mobile Telecommunication System (3G UMTS)) is growing exponentially and gaining popularity, and is predicted to expose new revenue streams for mobile network operators. However, the success of these video applications over wireless access networks very much depend on meeting the user’s Quality of Service (QoS) requirements. Thus, it is highly desirable to be able to predict and, if appropriate, to control video quality to meet user’s QoS requirements. Video quality is affected by distortions caused by the encoder and the wireless access network. The impact of these distortions is content dependent, but this feature has not been widely used in existing video quality prediction models. The main aim of the project is the development of novel and efficient models for video quality prediction in a non-intrusive way for low bitrate and resolution videos and to demonstrate their application in QoS-driven adaptation schemes for mobile video streaming applications. This led to five main contributions of the thesis as follows:(1) A thorough understanding of the relationships between video quality, wireless access network (UMTS and WLAN) parameters (e.g. packet/block loss, mean burst length and link bandwidth), encoder parameters (e.g. sender bitrate, frame rate) and content type is provided. An understanding of the relationships and interactions between them and their impact on video quality is important as it provides a basis for the development of non-intrusive video quality prediction models.(2) A new content classification method was proposed based on statistical tools as content type was found to be the most important parameter. (3) Efficient regression-based and artificial neural network-based learning models were developed for video quality prediction over WLAN and UMTS access networks. The models are light weight (can be implemented in real time monitoring), provide a measure for user perceived quality, without time consuming subjective tests. The models have potential applications in several other areas, including QoS control and optimization in network planning and content provisioning for network/service providers.(4) The applications of the proposed regression-based models were investigated in (i) optimization of content provisioning and network resource utilization and (ii) A new fuzzy sender bitrate adaptation scheme was presented at the sender side over WLAN and UMTS access networks. (5) Finally, Internet-based subjective tests that captured distortions caused by the encoder and the wireless access network for different types of contents were designed. The database of subjective results has been made available to research community as there is a lack of subjective video quality assessment databases.Partially sponsored by EU FP7 ADAMANTIUM Project (EU Contract 214751

Building self-optimized communication systems based on applicative cross-layer information

This article proposes the Implicit Packet Meta Header(IPMH) as a standard method to compute and represent common QoS properties of the Application Data Units (ADU) of multimedia streams using legacy and proprietary streams’ headers (e.g. Real-time Transport Protocol headers). The use of IPMH by mechanisms located at different layers of the communication architecture will allow implementing fine per-packet selfoptimization of communication services regarding the actual application requirements. A case study showing how IPMH is used by error control mechanisms in the context of wireless networks is presented in order to demonstrate the feasibility and advantages of this approach

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

Effect of Video Streaming Space–Time Characteristics on Quality of Transmission over Wireless Telecommunication Networks

The spate in popularity of multimedia applications has led to the need for optimization of bandwidth allocation and usage in telecommunication networks. Modern telecommunication networks should by their definition be able to maintain the quality of different applications with different Quality of Service (QoS) levels. QoS requirements are generally dependent on the parameters of network and application layers of the OSI model. At the application layer QoS depends on factors such as resolution, bit rate, frame rate, video type, audio codecs, etc. At the network layer, distortions such as delay, jitter, packet loss, etc. are introduced. This paper presents simulation results of modeling video streaming over wireless communications networks. The differences in spatial and time characteristics of the different subject groups were taken into account. Analysis of the influence of bit error rate (BER) and bit rate for video quality is also presented. Simulation showed that different video subject groups affect the perceived quality differently when transmitted over networks. We show conclusively that in a transmission network with a small error probabilities (BER = 10-6, BER = 10-5), the minimum bit rate (128 kbps) guarantees an acceptable video quality, corresponding to MOS > 3 for all types of frames

Smart resource allocation for improving QoE in IP Multimedia Subsystems

[EN] IP Multimedia Subsystem (IMS) is a robust multimedia service. IMS becomes more important when delivering multimedia services. Multimedia service providers can benefit from IMS to ensure a good QoE (Quality of Experience) to their customers with minimal resources usage. In this paper, we propose an intelligent media distribution IMS system architecture for delivering video streaming. The system is based primarily on uploading a multimedia file to a server in the IMS. Later, other users can download the uploaded multimedia file from the IMS. In the system, we also provide the design of the heuristic decision methods and models based on probability distributions. Thus, our system takes into account the network parameters such as bandwidth, jitter, delay and packet loss that influence the QoE of the end -users. Moreover, we have considered the other parameters of the energy consumption such as CPU, RAM, temperature and number connected users that impact the result of the QoE. All these parameters are considered as input to our proposal management system. The measurements taken from the real test bench show the real performance and demonstrate the success of the system about ensuring the upload speed of the multimedia file, guaranteeing the QoE of end users and improving the energy efficiency of the IMS.This work has been partially supported by the "Ministerio de Ciencia e Innovation", through the "Plan Nacional de I+D+i 2008-2011" in the "Subprograma de Proyectos de Investigation Fundamental", project TEC2011-27516, and by the Polytechnic University of Valencia, though the PAID-15-11 multidisciplinary projects.Canovas Solbes, A.; Taha, M.; Lloret, J.; Tomás Gironés, J. (2018). Smart resource allocation for improving QoE in IP Multimedia Subsystems. Journal of Network and Computer Applications. 104:107-116. https://doi.org/10.1016/j.jnca.2017.12.020S10711610

SoftCast: Clean-slate Scalable Wireless Video

Video broadcast and mobile video challenge the conventional wireless design. In broadcast and mobile scenarios the bit rate supported by the channel differs across receivers and varies quickly over time. The conventional design however forces the source to pick a single bit rate and degrades sharply when the channel cannot not support the chosen bit rate. This paper presents SoftCast, a clean-slate design for wireless video where the source transmits one video stream that each receiver decodes to a video quality commensurate with its specific instantaneous channel quality. To do so, SoftCast ensures the samples of the digital video signal transmitted on the channel are linearly related to the pixels' luminance. Thus, when channel noise perturbs the transmitted signal samples, the perturbation naturally translates into approximation in the original video pixels. Hence, a receiver with a good channel (low noise) obtains a high fidelity video, and a receiver with a bad channel (high noise) obtains a low fidelity video. We implement SoftCast using the GNURadio software and the USRP platform. Results from a 20-node testbed show that SoftCast improves the average video quality (i.e., PSNR) across broadcast receivers in our testbed by up to 5.5dB. Even for a single receiver, it eliminates video glitches caused by mobility and increases robustness to packet loss by an order of magnitude

Adaptive Streaming in Mobile Network

Mobile ecommerce is immersed rapid familiar to other high-flying Internet markets. With the fast developing of wireless connections and Internet, electronic commerce more and more moves to mobile environment. Streaming, as a rapid growing application in Internet, will be more used in mobile ecommerce. In this paper, we’ll review the network protocol used in mobile ecommerce and streaming technology. An optimized architecture is given based on MPEG-4 and Mobile Ipv6. The core streaming protocol used in this architecture is RTSP/RTP proposed by IETF. This system gives one possible implementation of streaming over wireless network. Two key bottlenecks we found in this project are wireless bandwidth and mobile client power. To avoid the two problems, self-adaptive methodology is used. Let streaming application be adaptive to the wireless network environment to improve streaming performance