Virtual RTCP: A Case Study of Monitoring and Repair for UDP-based IPTV Systems

IPTV systems have seen widespread deployment, but often lack robust mechanisms for monitoring the quality of experience. This makes it difficult for network operators to ensure that their services match the quality of traditional broadcast TV systems, leading to consumer dissatisfaction. We present a case study of virtual RTCP, a new framework for reception quality monitoring and reporting for UDP-encapsulated MPEG video delivered over IP multicast. We show that this allows incremental deployment of reporting infrastructure, coupled with effective retransmission-based packet loss repair

No-reference bitstream-based visual quality impairment detection for high definition H.264/AVC encoded video sequences

Ensuring and maintaining adequate Quality of Experience towards end-users are key objectives for video service providers, not only for increasing customer satisfaction but also as service differentiator. However, in the case of High Definition video streaming over IP-based networks, network impairments such as packet loss can severely degrade the perceived visual quality. Several standard organizations have established a minimum set of performance objectives which should be achieved for obtaining satisfactory quality. Therefore, video service providers should continuously monitor the network and the quality of the received video streams in order to detect visual degradations. Objective video quality metrics enable automatic measurement of perceived quality. Unfortunately, the most reliable metrics require access to both the original and the received video streams which makes them inappropriate for real-time monitoring. In this article, we present a novel no-reference bitstream-based visual quality impairment detector which enables real-time detection of visual degradations caused by network impairments. By only incorporating information extracted from the encoded bitstream, network impairments are classified as visible or invisible to the end-user. Our results show that impairment visibility can be classified with a high accuracy which enables real-time validation of the existing performance objectives

Real-Time Monitoring of Video Quality in IP Networks

This paper investigates the problem of assessing the quality of video transmitted over IP networks. Our goal is to develop a methodology that is both reasonably accurate and simple enough to support the large-scale deployments that the increasing use of video over IP are likely to demand. For that purpose, we focus on developing an approach that is capable of mapping network statistics, e.g., packet losses, available from simple measurements, to the quality of video sequences reconstructed by receivers. A first step in that direction is a loss-distortion model that accounts for the impact of network losses on video quality, as a function of application-specific parameters such as the video codec and loss recovery technique, coded bit rate, packetization, video characteristics, etc. The model, although accurate, is poorly suited to large-scale, on-line monitoring, because of its dependency on many parameters that are difficult to estimate in real-time. As a result, we introduce a relative quality metric that bypasses this problem by measuring video quality against a quality benchmark that the network is expected to provide. The approach offers a lightweight video quality monitoring solution that is suitable for large-scale deployments. We assess its feasibility and accuracy through extensive simulations and experiments

Real-Time Monitoring of Video Quality in IP Networks

This paper investigates the problem of assessing the quality of video transmitted over IP networks. Our goal is to develop a methodology that is both reasonably accurate and simple enough to support the large-scale deployments that the increasing use of video over IP are likely to demand. For that purpose, we focus on developing an approach that is capable of mapping network statistics, e.g., packet losses, available from simple measurements, to the quality of video sequences reconstructed by receivers. A first step in that direction is a loss-distortion model that accounts for the impact of network losses on video quality, as a function of application-specific parameters such as video codec, loss recovery technique, coded bit rate, packetization, video characteristics, etc. The model, although accurate, is poorly suited to large-scale, on-line monitoring, because of its dependency on parameters that are difficult to estimate in real-time. As a result, we introduce a relative quality metric (rPSNR) that bypasses this problem by measuring video quality against a quality benchmark that the network is expected to provide. The approach offers a lightweight video quality monitoring solution that is suitable for large-scale deployments. We assess its feasibility and accuracy through extensive simulations and experiments

Network distributed 3D video quality monitoring system

This project description presents a research and development work whose primary goal was the design and implementation of an Internet Protocol (IP) network distributed video quality assessment tool. Even though the system was designed to monitor H.264 three-dimensional (3D) stereo video quality it is also applicable to di erent formats of 3D video (such as texture plus depth) and can use di erent video quality assessment models making it easily customizable and adaptable to varying conditions and transmission scenarios. The system uses packet level data collection done by a set of network probes located at convenient network points, that carry out packet monitoring, inspection and analysis to obtain information about 3D video packets passing through the probe's locations. The information gathered is sent to a central server for further processing including 3D video quality estimation based on packet level information. Firstly an overview of current 3D video standards, their evolution and features is presented, strongly focused on H.264/AVC and HEVC. Then follows a description of video quality assessment metrics, describing in more detail the quality estimator used in the work. Video transport methods over the Internet Protocol are also explained in detail as thorough knowledge of video packetization schemes is important to understand the information retrieval and parsing performed at the front stage of the system, the probes. After those introductory themes are addressed, a general system architecture is shown, explaining all its components and how they interact with each other. The development steps of each of the components are then thoroughly described. In addition to the main project, a 3D video streamer was created to be used in the implementation tests of the system. This streamer was purposely built for the present work as currently available free-domain streamers do not support 3D video streaming. The overall result is a system that can be deployed in any IP network and is exible enough to help in future video quality assessment research, since it can be used as a testing platform to validate any proposed new quality metrics, serve as a network monitoring tool for video transmission or help to understand the impact that some network characteristics may have on video quality

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

Live media production: multicast optimization and visibility for clos fabric in media data centers

Media production data centers are undergoing a major architectural shift to introduce digitization concepts to media creation and media processing workflows. Content companies such as NBC Universal, CBS/Viacom and Disney are modernizing their workflows to take advantage of the flexibility of IP and virtualization. In these new environments, multicast is utilized to provide point-to-multi-point communications. In order to build point-to-multi-point trees, Multicast has an established set of control protocols such as IGMP and PIM. The existing multicast protocols do not optimize multicast tree formation for maximizing network throughput which lead to decreased fabric utilization and decreased total number of admitted flows. In addition, existing multicast protocols are not bandwidth-aware and could cause links to over-subscribe leading to packet loss and lower video quality. TV production traffic patterns are unique due to ultra high bandwidth requirements and high sensitivity to packet loss that leads to video impairments. In such environments, operators need monitoring tools that are able to proactively monitor video flows and provide actionable alerts. Existing network monitoring tools are inadequate because they are reactive by design and perform generic monitoring of flows with no insights into video domain. The first part of this dissertation includes a design and implementation of a novel Intelligent Rendezvous Point algorithm iRP for bandwidth-aware multicast routing in media DC fabrics. iRP utilizes a controller-based architecture to optimize multicast tree formation and to increase bandwidth availability in the fabric. The system offers up to 50\% increase in fabric capacity to handle multicast flows passing through the fabric. In the second part of this dissertation, DiRP algorithm is presented. DiRP is based on a distributed decision-making approach to achieve multicast tree capacity optimization while maintaining low multicast tree setup time. DiRP algorithm is tested using commercially available data center switches. DiRP algorithm offers substantially lower path setup time compared to centralized systems while maintaining bandwidth awareness when setting up the fabric. The third part of this dissertation studies the utilization of machine learning algorithms to improve on multicast efficiency in the fabric. The work includes implementation and testing of LiRP algorithm to increase iRP\u27s fabric efficiency by implementing k-fold cross validation method to predict future multicast group memberships for time-series analysis. Testing results confirm that LiRP system increases the efficiency of iRP by up to 40\% through prediction of multicast group memberships with online arrival. In the fourth part of this dissertation, The problem of live video monitoring is studied. Existing network monitoring tools are either reactive by design or perform generic monitoring of flows with no insights into video domain. MediaFlow is a robust system for active network monitoring and reporting of video quality for thousands of flows simultaneously using a fraction of the cost of traditional monitoring solutions. MediaFlow is able to detect and report on integrity of video flows at a granularity of 100 mSec at line rate for thousands of flows. The system increases video monitoring scale by a thousand-fold compared to edge monitoring solutions

Management of Digital Video Broadcasting Services in Open Delivery Platforms

The future of Digital Video Broadcasting (DVB) is moving towards solutions offering an efficient way of carrying interactive IP multimedia services over digital terrestrial broadcasting networks to handheld terminals. One of the most promising technologies is Digital Video Broadcasting-Handheld (DVB-H), at present under standardisation. Services deployed via this type of DVB technologies should enjoy reliability comparable to TV services and high quality standards. However, the market at present does not provide effective and economical solutions for the deployment of such services over multi-domain IP networks, due to their high level of unreliability. This paper focuses on service management, service level agreement (SLA) and network performance requirements of DVB-H services. Experimental results are presented concerning QoS sensitivity to network performance of DVB-H services delivered over a multi-domain IP network. Moreover, a solution for efficient and cost effective service management via QoS monitoring and control and network SLA design is proposed. The solution gives DVB-H operators the possibility of fully managing service QoS without being tied to third party operators

Video streaming

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