Adaptive Live Video Streaming by Priority Drop

In this paper we explore the use of Priority-progress streaming (PPS) for video surveillance applications. PPS is an adaptive streaming technique for the delivery of continuous media over variable bit-rate channels. It is based on the simple idea of reordering media components within a time window into priority order before transmission. The main concern when using PPS for live video streaming is the time delay introduced by reordering. In this paper we describe how PPS can be extended to support live streaming and show that the delay inherent in the approach can be tuned to satisfy a wide range of latency constraints while supporting fine-grain adaptation

Resource allocation and adaptive scheduling for scalable video streaming

The obvious recent advances in areas such as video compression and network architectures allow for the deployment of novel video distribution applications. These have the potential to provide ubiquitous media access to end users. In recent years, applications based on audio and video streaming have turned out to be immensely popular and the Internet has become the most widely used vector for media content distribution, due to its high availability and connectivity. However, the nature of the Internet infrastructure is not adapted to the specific characteristics of multimedia traffic, which presents a certain tolerance to losses, but strict delay and high bandwidth requirements. In this thesis, our goal is to improve the efficiency of media delivery over the existing network architecture. In order to do so we consider the delivery of scalable video in three main delivery scenarios, namely one-to-one client server architectures, one-to-many broadcasting architectures, and many-to-one distributed streaming architectures. First, we propose a distributed media-friendly rate allocation algorithm for the delivery of both finely and coarsely scalable video streams. Unlike existing solutions, our algorithm explicitly takes the characteristics of media streams into consideration. As a result, it provides rate allocations that better fit the heterogeneous characteristics of media streams. We outline an implementation that is robust to random feedback delays and that permits a scalable deployment of the algorithm. The rate allocation that is computed by our algorithm achieves network stability and high bandwidth utilization. It moreover allows to maximize the average received quality for all streams that are delivered in the network. While considering the transmission of coarsely layered streams, we derive conditions on the encoding rates of the video layers. These conditions depend on the allowed end-to-end delay and on the rate allocation algorithm that controls the sending rates. They allow us to take full advantage of the allocated transmission rates. Second, we investigate the problem of jointly addressing the needs of multiple receivers that consume different versions of a layered media stream in a broadcasting scenario. We provide optimal scheduling algorithms that jointly optimize the playback delay and the buffer occupancy at all of these receivers when the used channel is known. Furthermore we analyze low complexity heuristics based optimization techniques, which provide close to optimal results when only limited channel knowledge is available. Finally, we explore the possibility to exploit the inherent network diversity that is provided by the Internet infrastructure. In particular, we consider media delivery schemes where multiple senders are available for the transmission of a scalable video stream to a single client. Such an architecture is referred to as a distributed streaming architecture. It has the benefit of aggregating multiple unreliable channels into a single more robust channel with high availability. Through the use of Fountain codes, we are able to transform the distributed streaming problem into a rate allocation problem of lower complexity. The solution to this problem is shown to depend not only on the average packet loss rate, but also on the average length of packet loss bursts that are observed on each of the available channels. The coding scheme that we suggest enables our system to adapt the streamed content to the network characteristics, as well as to the needs of the receiving client

Efficient and Effective Schemes for Streaming Media Delivery

The rapid expansion of the Internet and the increasingly wide deployment of wireless networks provide opportunities to deliver streaming media content to users at anywhere, anytime. To ensure good user experience, it is important to battle adversary effects, such as delay, loss and jitter. In this thesis, we first study efficient loss recovery schemes, which require pure XOR operations. In particular, we propose a novel scheme capable of recovering up to 3 packet losses, and it has the lowest complexity among all known schemes. We also propose an efficient algorithm for array codes decoding, which achieves significant throughput gain and energy savings over conventional codes. We believe these schemes are applicable to streaming applications, especially in wireless environments. We then study quality adaptation schemes for client buffer management. Our control-theoretic approach results in an efficient online rate control algorithm with analytically tractable performance. Extensive experimental results show that three goals are achieved: fast startup, continuous playback in the face of severe congestion, and maximal quality and smoothness over the entire streaming session. The scheme is later extended to streaming with limited quality levels, which is then directly applicable to existing systems

Scalable Video Streaming over the Internet

The objectives of this thesis are to investigate the challenges on video streaming, to explore and compare different video streaming mechanisms, and to develop video streaming algorithms that maximize visual quality. To achieve these objectives, we first investigate scalable video multicasting schemes by comparing layered video multicasting with replicated stream video multicasting. Even though it has been generally accepted that layered video multicasting is superior to replicated stream multicasting, this assumption is not based on a systematic and quantitative comparison. We argue that there are indeed scenarios where replicated stream multicasting is the preferred approach. We also consider the problem of providing perceptually good quality of layered VBR video. This problem is challenging, because the dynamic behavior of the Internet's available bandwidth makes it difficult to provide good quality. Also a video encoded to provide a consistent quality exhibits significant data rate variability. We are, therefore, faced with the problem of accommodating the mismatch between the available bandwidth variability and the data rate variability of the encoded video. We propose an optimal quality adaptation algorithm that minimizes quality variation while at the same time increasing the utilization of the available bandwidth. Finally, we investigate the transmission control protocol (TCP) for a transport layer protocol in streaming packetized media data. Our approach is to model a video streaming system and derive relationships under which the system employing the TCP protocol achieves desired performance. Both simulation results and the Internet experimental results validate this model and demonstrate the buffering delay requirements achieve desired video quality with high accuracy. Based on the relationships, we also develop realtime estimation algorithms of playout buffer requirements.Ph.D.Committee Chair: Mostafa H. Ammar; Committee Co-Chair: Yucel Altunbasak; Committee Member: Chuanyi Ji; Committee Member: George Riley; Committee Member: Henry Owen; Committee Member: Jack Brassi

Joint Playback Delay and Buffer Optimization in Scalable Video Streaming

This paper addresses the problem of the transmission of scalable video streams to a set of heterogeneous clients through a common bottleneck channel. The packet scheduling policy is typically crucial in such systems that target smooth media playback at all the receivers. In particular, the playback delays and the transmission strategy for the packets of the different layers have to be chosen carefully. When the same video is sent simultaneously to multiple clients that subscribe to different parts of the stream, the playback delay cannot be jointly minimized for all the clients. We therefore propose delay optimization strategies along with low complexity solutions for a fair distribution of the delay penalty among the different receivers. Once the delays are selected, we show that there exists a unique scheduling solution that minimizes the buffer occupancy at all the receivers. We derive an algorithm for computing the optimal sending trace, and we show that optimal scheduling has to respect the order of the packets in each media layer. Interestingly enough, solving both delay and buffer optimization problems sequentially leads to a jointly optimal solution when the channel is known. We finally propose a simple rate adaptation mechanism that copes with unexpected channel bandwidth variations by controlling the sending rate and dropping layers when the bandwidth becomes insufficient. Experimental results shows that it permits to reach close to optimal performances even if the channel knowledge is reduced. Rate adaptation provides an interesting alternative to conservative scheduling strategies, providing minor and controllable quality variations, but with a higher resulting average quality

Adaptive delivery of real-time streaming video

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.Includes bibliographical references (p. 87-92).While there is an increasing demand for streaming video applications on the Internet, various network characteristics make the deployment of these applications more challenging than traditional Internet applications like email and the Web. The applications that transmit data over the Internet must cope with the time-varying bandwidth and delay characteristics of the Internet and must be resilient to packet loss. This thesis examines these challenges and presents a system design and implementation that ameliorates some of the important problems with video streaming over the Internet. Video sequences are typically compressed in a format such as MPEG-4 to achieve bandwidth efficiency. Video compression exploits redundancy between frames to achieve higher compression. However, packet loss can be detrimental to compressed video with interdependent frames because errors potentially propagate across many frames. While the need for low latency prevents the retransmission of all lost data, we leverage the characteristics of MPEG-4 to selectively retransmit only the most important data in order to limit the propagation of errors. We quantify the effects of packet loss on the quality of MPEG-4 video, develop an analytical model to explain these effects, and present an RTP-compatible protocol-which we call SR-RTP--to adaptively deliver higher quality video in the face of packet loss. The Internet's variable bandwidth and delay make it difficult to achieve high utilization, Tcp friendliness, and a high-quality constant playout rate; a video streaming system should adapt to these changing conditions and tailor the quality of the transmitted bitstream to available bandwidth. Traditional congestion avoidance schemes such as TCP's additive-increase/multiplicative/decrease (AIMD) cause large oscillations in transmission rates that degrade the perceptual quality of the video stream. To combat bandwidth variation, we design a scheme for performing quality adaptation of layered video for a general family of congestion control algorithms called binomial congestion control and show that a combination of smooth congestion control and clever receiver-buffered quality adaptation can reduce oscillations, increase interactivity, and deliver higher quality video for a given amount of buffering. We have integrated this selective reliability and quality adaptation into a publicly available software library. Using this system as a testbed, we show that the use of selective reliability can greatly increase the quality of received video, and that the use of binomial congestion control and receiver quality adaptation allow for increased user interactivity and better video quality.by Nicholas G. Feamster.M.Eng

Packet Selection and Scheduling for Multipath Video Streaming

This paper addresses the problem of choosing the best streaming policy for distortion optimal multipath video delivery, under delay constraints. The streaming policy consists in a joint selection of the video packets to be transmitted, as well as their sending time, and the transmission path. A simple streaming model is introduced, which takes into account the video packet importance, and the dependencies among packets, and allows to compute the quality perceived by the receiver, as a function of the streaming policy. We derive an optimization problem based on the video abstraction model, under the assumption that the server knows, or can predict the state of the network. A detailed analysis of the timing constraints in multipath video streaming provides helpful insights that lead to an efficient algorithm to solve the NP-hard streaming policy optimization problem. We eventually propose a fast heuristic-based algorithm, that still provides close to optimal performance. Thanks to its limited complexity, this novel algorithm is finally demonstrated in live streaming scenarios, where it only induces a negligible distortion penalty compared to an optimal strategy. Simulation results finally show that the proposed scheduling solutions perform better than common scheduling algorithms, and represent very efficient multipath streaming strategies for both stored and live video services

TECHNIQUES AND PROTOCOLS FOR DISTRIBUTED MEDIA STREAMING

Ph.DDOCTOR OF PHILOSOPH

Packet prioritizing and delivering for multimedia streaming

Ph.DDOCTOR OF PHILOSOPH