The focus of this paper is on improving the quality of streaming video transmitted over the Internet. The approach we investigate assumes the availability of multiple paths between the source and the destination, and dynamically selects the best one. Although this is not a new concept, our contribution is in estimating the "goodness " of a path from the perspective of the video stream, instead of relying only on raw network performance measures. The paper starts by showing that the use of raw network performance data to control path switching decisions can often result in poor choices from an application perspective, and then proceeds to develop a practical approach for evaluating, in real-time, the performance of different paths in terms of video quality. Those estimates are used to continuously select the path that yields the best possible transmission conditions for video streaming applications. We demonstrate the feasibility and performance of the scheme through experiments involving different types of videos.

We analyze the susceptibility of the Internet to random faults, malicious attacks, and mixtures of faults and attacks. We analyze actual Internet data, as well as simulated data created with network models. The network models generalize previous research, and allow generation of graphs ranging from uniform to preferential, and from static to dynamic. We introduce new metrics for analyzing the connectivity and performance of networks which improve upon metrics used in earlier research. Previous research has shown that preferential networks like the Internet are more robust to random failures compared to uniform networks. We find that preferential networks, including the Internet, are more robust only when more than 95% of failures are random faults, and robustness is measured with average diameter. The advantage of preferential networks disappears with alternative metrics, and when a small fraction of faults are attacks. We also identify dynamic characteristics of the Internet which can be used to create improved network models. This model should allow more accurate analysis for the future Internet, for example facilitating the design of network protocols with optimal performance in the future, or predicting future attack and fault tolerance. We find that the Internet is becoming more preferential as it evolves. The average diameter has been stable or even decreasing as the number of nodes has been increasing. The Internet is becoming more robust to random failures over time, but has also become more vulnerable to attacks.

There has been an increased interest in adaptive video quality control and dynamically adjusting the output video bit rate based on the status of the network. However, network-level performance parameters cannot accurately reflect the video quality perceived by the end users. Our goal is to investigate an adaptive perceptual video quality control mechanism based on an application-level perceptual video quality scheme. In this paper we investigate perceptual objective quality assessment technologies and use them to exploit the relationships between perceptual video quality, output bit rate, and quantization scales of video encoders. We also implemented a real time Video over IP (VIP) network application that uses a feedback channel to relay measurements, taken at the end user, to the source side, to enable the calculation of the perceptual video quality degradation caused by IP packet loss. Using this experimental setup, we were able to investigate appropriate rules for adaptive perceptual video quality control based on an application-level perceptual video quality scheme. 1.

Indiscriminated packet discards strongly degrade the quality per- ceived by end users of MPEG video transmissions. This paper inves- tigates different Quality of Service (QoS) schemes and the tradeoffs of jointly adopting such schemes to improve the delivery quality of an MPEG stream. From an analytical model, we evaluate the impact of frame losses on the quality of MPEG streams and on the waste of network resources. Our assessment considers issues such as the use of redundancy by applying a Forward Error Correction (FEC) scheme to tolerate losses, the changing of the compression factor in MPEG encod- ing, the unequal protection of MPEG frames in a Differentiated Services environment, and how to evaluate the impact of network losses onto application quality. Results provide predicted bounds on the quality to be expected by end users as well as guidelines on how to take the best advantage from the joint adoption of the investigated QoS schemes.

Home networks are becoming ubiquitous, especially since the advent of wireless technologies such as IEEE 802.11. Coupled with this, there is an increase in the number of broadband-connected homes, and many new services are being deployed by broadband providers, such as TV and VoIP. The home network is thus becoming the ‘media hub ’ of the house. This trend is expected to continue, and to expand into the Consumer Electronics (CE) market as well. This means new devices that can tap into the network in order to get their data, such as wireless TV sets, gaming consoles, tablet PCs etc. In this paper, we address the issue of evaluating the QoS provided for those media services, from the end-user’s point of view. We present a performance analysis of the home network in terms of perceived quality, and show how our real-time quality assessment technique can be used to dynamically control existing QoS mechanisms. This participates to minimizing resource consumption by tuning the appropriate QoS affecting parameters in order to keep the perceived quality (the ultimate target) within acceptable bounds.

consumer, there will be exponential growth in the distribution and hosting of media on the Internet. We expect this growth to parallel that of HTTP traffic. Our position is that we need to confront the issues related to the potential exponential growth in the number of media sources and services. Further, we believe that significantly higher quality streaming and context-sensitive personalization of multimedia services are key enablers of this whole technology area. Our vision differs from the delivery of video-on-demand services because we believe that there will be a vast number of sources of copyleft content. In this paper we focus on four key areas: the distributed discovery of content; the concurrent manipulation of multiple media streams; media sensitive mechanisms for providing end-to-end services over the Internet; and the subjective assessment of delivered media quality.

Application-level multicast networks overlaid on unicast IP networks are increasingly gaining in importance. While there have been several proposals for overlay multicast networks, very few of them focus on the stringent requirements of real-time applications such as streaming media. We propose RITA (Receiver Initiated Timely Adaptation) framework for an e#cient overlay multicast infrastructure. RITA is based on a combination of landmark clustering and RTT measurements, and is particularly suitable for multimedia real-time applications. Our goal is to balance the networkoriented goals of building an e#cient multicast tree with the application-oriented goals of providing good QoS with minimal disruptions. Using accurate global soft state information tables, our approach promptly constructs and reconfigures high quality trees. A distinguishing feature of our approach is that the tree reconfiguration is initiated justin -time by the application client at the receiver when the media quality falls below a specific threshold. The goal is to achieve dynamic tree reconfiguration with very low switching delay such that end users do not perceive any application performance degradation.

Streaming multimedia quality is impacted by two main factors: capacity constraint and packet loss. To match the capacity constraint while preserving real-time playout, media scaling can be used to discard the encoded multimedia content that has the least impact on perceived video quality. To limit the impact of lost packets, repair techniques, e.g. forward error correction (FEC), can be used to repair frames damaged by packet loss. However, adding data to facilitate repair requires further reduction of the original multimedia data, making the decision of how much repair data to use of critical importance. Assuming a limited network capacity and the availability of an estimate of the current packet loss rate along a flow path, selecting the best distribution of FEC packets for video frames with inherent interframe encoding dependencies can be cast as a constraint optimization problem that attempts to optimize the quality of the video stream. This thesis presents an Adjusting Repair and Media scaling with Operations

Conducting quality assessment for streaming media services, particularly from the end user perspective, has not been widely addressed by the network research community and remains a hard problem. In this paper we discuss the general problem of assessing the quality of streaming media in a large-scale IP network. This work presents two main contributions. First, we specify a new measurement and assessment architecture that can flexibly support the needs of different classes of assessment consumers while supporting both new and existing measurements that can be correlated with user perceptions of media stream quality. Second, we demonstrate that a prototype implementation of this architecture can be used to assess a user's perceived quality of a media stream, by judicious choice and assessment of objective metrics. We conclude by discussing how this architecture can be used to predict future periods of stream quality degradation.

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