Enhancing aggregate QoS for video streaming

The IETF's Differentiated Services architecture is designed to provide different types or levels of service for Internet traffic. One of its key features is that traffic flows are aggregated so that routers in the core network only need to distinguish a relatively small number of aggregate flows, even if those flows consist of hundreds or thousands of individual flows. However, network-level QoS differentiation may not satisfy the requirements of many QoS-sensitive applications such as live video streaming, where end-to-end delay and reliability must be guaranteed.

This paper investigates application-level service differentiation for MPEG video streaming in a Diff-Serv-aware MPLS network infrastructure, along with routing support at the network layer. Based on the fact that MPEG video has become one of the most popular formats for Internet (wired and wireless) users, our approach enhances aggregate QoS for video streaming by employing existing application-level knowledge of the MPEG video structure; therefore it requires neither a new video compression algorithm nor additional bandwidth. Several MPEG video dispersion models are proposed and analyzed. Simulation results show that two such strategies are superior to the other tested. In addition, a new routing scheme is proposed to support searching the ‘best’ paths for efficient multi-path video streaming. Through extensive simulations, we demonstrate that our approaches improve the aggregate QoS of MPEG video streams, as well as overall network efficiency.     

ATM网络中全动态视频源的二次建模

通过对ATM网络视频业务传输性能及其建模分析,针对高运动性（即全动态）视频源的建模,给出基于块的MPEG运动估计算法,提出一种非线性模型。基于自回归在GOP层对MPEG视频流进行二次建模。仿真表明,该文提出的NAR模型能准确预测具有适度运动性的实际MPEG流,对具有高运动性的流在不同的负荷和缓冲器的条件下提供可接受的预测。     

An efficient fully unsupervised video object segmentation scheme using an adaptive neural-network classifier architecture

In this paper, an unsupervised video object (VO) segmentation and tracking algorithm is proposed based on an adaptable neural-network architecture. The proposed scheme comprises: 1) a VO tracking module and 2) an initial VO estimation module. Object tracking is handled as a classification problem and implemented through an adaptive network classifier, which provides better results compared to conventional motion-based tracking algorithms. Network adaptation is accomplished through an efficient and cost effective weight updating algorithm, providing a minimum degradation of the previous network knowledge and taking into account the current content conditions. A retraining set is constructed and used for this purpose based on initial VO estimation results. Two different scenarios are investigated. The first concerns extraction of human entities in video conferencing applications, while the second exploits depth information to identify generic VOs in stereoscopic video sequences. Human face/ body detection based on Gaussian distributions is accomplished in the first scenario, while segmentation fusion is obtained using color and depth information in the second scenario. A decision mechanism is also incorporated to detect time instances for weight updating. Experimental results and comparisons indicate the good performance of the proposed scheme even in sequences with complicated content (object bending, occlusion).     

Adaptive filtering of MPEG system streams in IP networks

Congestion and large differences in available link bandwidth create challenges for the design of applications that want to deliver high quality video over the Internet. We present an efficient adaptive filter for MPEG System streams that can be placed in the network (e.g., as an active service). This filter adjusts the bandwidth demands of an MPEG System stream to the available bandwidth without transcoding while maintaining synchronization between the streams embedded in the MPEG System. The filter is network-friendly: it is fair with respect to other (TCP) competing streams and it avoids generating bursty traffic. This paper presents the system architecture and an evaluation of our implementation in three different operating environments: a networking testbed in a laboratory environment, a home-user scenario (DSL line with 640 Kbit/s), and a wide area network covering the Atlantic (server in Europe, client in the US). Moreover we examine the network-friendliness of the adaptation protocol and the relationship between the quality of the received continuous media and the protocol's aggressiveness. Our architecture is based on efficient MPEG System filtering to achieve high-quality video over best-effort networks.Effort sponsored in part by the Advanced Research Projects Agency and Rome Laboratory, Air Force Materiel Command, USAF, under agreement number F30602-96-1-0287. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon.The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Advanced Research Projects Agency, Rome Laboratory, or the U.S. Government.     

Ant-based routing for wireless multimedia sensor networks using multiple QoS metrics

In wireless sensor networks, most routing protocols consider energy savings as the main objective and assume data traffic with unconstrained delivery requirements to be a given. However, the introduction of video and imaging sensors unveils additional challenges. The transmission of video and imaging data requires both energy efficiency and QoS assurance (end-to-end delay and packet loss requirements), in order to ensure the efficient use of sensor resources as well as the integrity of the information collected. This paper presents a QoS routing model for Wireless Multimedia Sensor Networks (WMSN). Moreover, based on the traditional ant-based algorithm, an ant-based multi-QoS routing metric (AntSensNet) is proposed. The AntSensNet protocol builds a hierarchical structure on the network before choosing suitable paths to meet various QoS requirements from different kinds of traffic, thus maximizing network utilization, while improving its performance. In addition, AntSensNet is able to use a efficient multi-path video packet scheduling in order to get minimum video distortion transmission. Finally, extensive simulations are conducted to assess the effectiveness of this novel solution and a detailed discussion regarding the effects of different system parameters is provided. Compared to typical routing algorithms in sensor networks and the traditional ant-based algorithm, this new algorithm has better convergence and provides significantly better QoS for multiple types of services in wireless multimedia sensor networks.     

A Quality-Driven Cross-Layer Solution for MPEG Video Streaming Over WiMAX Networks

Extensive efforts have been focused on deploying broadband wireless networks. Providing mobile users with high speed network connectivity will let them run various multimedia applications on their wireless devices. Satisfying users with different quality-of-service requirements while optimizing resource allocation is a challenging problem. In this paper, we discuss the challenges and possible solutions for transmitting MPEG video streams over WiMAX networks. We will briefly describe the MPEG traffic model suggested by the WiMAX Forum. A cross-layer solution for enhancing the performance of WiMAX networks with respect to MPEG video streaming applications is explained. Our solution uses the characteristics of MPEG traffic to give priority to the more important frames and protect them against dropping. Besides, it is simple and compatible with the IEEE 802.16 standards and thus easily deployable. It is shown that the proposed solutions will improve the video quality over WiMAX networks.     

Traffic modeling, prediction, and congestion control for high-speednetworks: a fuzzy AR approach

In this study, a fuzzy autoregressive (fuzzy-AR) model is proposed to describe the traffic characteristics of high-speed networks. The fuzzy-AR model approximates a nonlinear time-variant process with a combination of several linear local AR processes using a fuzzy clustering method. We propose that the use of this fuzzy-AR model has greater potential for congestion control of packet network traffic. The parameter estimation problem in fuzzy-AR modeling is treated by a clustering algorithm developed from actual traffic data in high-speed networks. Based on the adaptive AR-prediction model and queueing theory, a simple congestion control scheme is proposed to provide an efficient traffic management for high-speed networks. Finally, using the actual Ethernet-LAN packet traffic data, several examples are given to demonstrate the validity of this proposed method for high-speed network traffic control     

基于模糊控制的ATM网络VBR视频传输平滑策略

VBR视频传输的突发性是影响ATM网络服务质量的关键因素,文中通过模糊控制方法对视频传输流量的阈值进行监控,实现了接入的平滑并可动态调整传输速度。文中以传输流量及这发级作为评价指标进行分析,结果表明VBR视频传输自适应平滑策略的实效性。     

An Integrated Framework for Efficient Transport of Real-Time MPEG Video over ATM Best Effort Service

This paper describes a framework for the transport of real-time multimedia traffic generated by MPEG-2 applications over ATM networks using an enhanced UBR best effort service (UBR+). Based on the factors affecting the picture quality during transmission, we propose an efficient and cost-effective ATM best effort delivery service. The proposed framework integrates three major components: 1) a dynamic frame-level priority assignment mechanism based on MPEG data structure and feedback from the network (DexPAS), 2) a novel audio-visual AAL5 SSCS with FEC (AV-SSCS), and 3) an intelligent packet video discard scheme named FEC-PSD, which adaptively and selectively adjusts cell drop levels to switch buffer occupancy, video cell payload type and forward error correction capability of the destination. The overall best-effort video delivery framework is evaluated using ATM network simulation and MPEG2 video traces. The ultimate goal of this framework is twofold: First, minimizing loss of critical video data with bounded end-to-end delay for arriving cells and second, reducing the bad throughput crossing the network during congestion. Compared to previous approaches, performance evaluation shows a good protection of Predictive coded (P-) and Bi-directional Predictive coded (B-) frames at the MPEG video slice layer.     

A real-time video multicast architecture for assured forwarding services

This paper presents our work on developing an architecture for multicasting real-time MPEG4 over IP networks that provide service differentiation. In particular, this work is targeted at assured forwarding (AF) style services. This work is an attempt to find a simple solution to the problem of multicast congestion control of real-time traffic by exploiting the service differentiation capabilities of AF networks. Our architecture assumes loss differentiation in the network and assumes the network's ability to provide explicit congestion notification messages to the sender. We do not consider policing/shaping at the edge routers. Rather, we consider a more general case where packet marking and flow control are provided at the senders. For this network model, we built an end-to-end architecture and developed a rate-adaptation algorithm that can operate in both unicast and multicast applications with a minor modification. The simulation results show how the rate-adaptation algorithm accommodates different receivers with different networking capabilities and provides receivers with different levels of quality by taking advantage of the queue management capabilities of the AF service. We test how the architecture scales to a large number of receivers, how multiple multicast sessions interact, and how it interacts with TCP.     

基于小波网络的非线性系统建模与控制

提出了种基于小波网络的非线性系统的建模和控制方法。使用小波网络对未知控制系统建立一步预测模型,基于Ｄｓａｖｉｄｏｎ最小二乘法得到自适应控制律。小波网络的权值由广义递推最小二乘法来学习,尺度参数和平移参数通过稳定的Ｄａｖｉｄｏｎ最小二乘法来获得。仿真结果表明了该方法的有效性。     

Feig快速DCT算法及其处理器的体系结构设计

离散余弦变换是ＪＰＥＧ和ＭＰＥＧ中的关键技术之一。当前ＭＰＥＧ的普遍应用是在解码中使用，一个解码的例子是ＶＣＤ，ＩＤＣＴ是静止／运动补偿帧解码的关键部分。为了要得到较好的性能，ＩＤＣＴ通常被硬件逻辑实现而嵌入产品中，但该方法有一个缺陷。那就是ＩＤＣＴ的硬件逻辑实现不能完成ＭＰＥＧ所需要的其它功能，如音频解码，视频／音频的比特流可变长度解码等等。文中提出的Ｆｅｉｇ快速ＤＣＴ算法的并行顺序指令流实现Ｉ     

Modeling and distributed simulation of a broadband-ISDN network

A distributed approach to communication network simulation using a network of workstations configured as a loosely coupled parallel processor to model and simulate the broadband integrated services digital network (B-ISDN) is proposed. In a loosely coupled parallel processor system, a number of concurrently executable processors communicate asynchronously using explicit messages over high-speed links. Since this architecture is similar to that of B-ISDN networks, it constitutes a realistic testbed for their modeling and simulation. The authors describe an implementation of this approach on 50 Sun workstations at Brown University. Performance results, based on representative B-ISDN networks and realistic traffic models, indicate that the distributed approach is efficient and accurate     

A recursive algorithm based on the extended Kalman filter for the training of feedforward neural models

The extended Kalman filter (EKF) is a well-known tool for the recursive parameter estimation of static and dynamic nonlinear models. In particular, the EKF has been applied to the estimation of the weights of feedforward and recurrent neural network models, i.e. to their training, and shown to be more efficient than recursive and nonrecursive first-order training algorithms; nevertheless, these first applications to the training of neural networks did not fully exploit the potentials of the EKF. In this paper, we analyze the specific influence of the EKF parameters for modeling problems, and propose a variant of this algorithm for the training of feedforward neural models which proves to be very efficient as compared to nonrecursive second-order algorithms. We test the proposed EKF algorithm on several static and dynamic modeling problems, some of them being benchmark problems, and which bring out the properties of the proposed algorithm.     

基于MPEG视频流的动态带宽分配算法

ATM是兴起的宽带网标准,基于报文的视频正是宽带网上的一个典型应用.变位率视频的传输方法为恒定的视频质量提供了可能,但是在传输过程中,报文的丢失、延迟和延迟抖动等因素都会影响视频质量,因此有必要提供QoS保证.提出了两种新的在ATM网上进行MPEG视频传输的动态带宽分配算法,一种是动态计算算法,另一种是动态虚拟缓存算法.在这些算法中,根据允许的丢包率,动态地调整MPEG视频带宽以保证QoS.     

一种无线实时流媒体增强型自适应FEC控制机制

无线网络动态的信道特性和带宽有限等特点,使得在无线环境下为流媒体应用提供QoS保证面临更大的挑战。提出一种用于无线实时流媒体传输的增强型自适应前向纠错控制策略,以提高接收方的播放质量。该策略采用跨层设计的方法,根据当前的网络状态,自适应地调整MPEG视频帧的发送速率,在视频源数据和冗余数据之间动态分配网络带宽。仿真结果表明,该策略能使接收方获得最大的可播放帧率,有效提高流媒体传输的可靠性和实时性。     

The periodic Markov modulated batch Bernoulli process and its application to MPEG video traffic

The Markov modulated batch Bernoulli process (MMBBP) is widely used for modeling a superposition of multiple voices and data at multiplexers in asynchronous transfer mode (ATM) networks, because the MMBBP has the time correlation property and its autocorrelation function is exponentially decaying. However, experimental studies on the MPEG (Motion Pictures Expert Group) video traffic show that its autocorrelation function is periodic as well as exponentially decaying. So, the MMBBP is not adequate to describe the MPEG video traffic.

In this paper, we propose a new stochastic process which we call the periodic Markov modulated batch Bernoulli process (P-MMBBP) to describe the MPEG video traffic adequately. We derive the autocorrelation function of the P-MMBBP and show that the autocorrelation functions of the P-MMBBP and the MPEG video traffic are of the same pattern. We also propose a simple way to match parameters of the P-MMBBP from real MPEG video traffic. We consider the P-MMBBP/D/1 queue and derive the queue length distribution analytically. From numerical results, we show that periodicity gives a significant effect on the tail behavior of the queue length distribution. We also compare tail probabilities obtained by using the P-MMBBP with those obtained by using the 2-state MMBBP. Our comparison shows that the use of the 2-state MMBBP underestimates tail probabilities.     

基于主动抛弃的MPEG—2 TS流速率控制算法

在网络传输能力不足以实时传输MPEG-2码流时，接收端的图象恢复质量会因为在网络传送中不可避免的、随机的数据丢失而严重下降，为了解决这一问题，提出了一种基于主动抛弃的MPEG-2 TS流速率控制算法，即在原始码流输送到网络前，根据预测的网络传输阻塞状况，预先主动抛弃部分不太重要的数据，从而使实际输出码率与可用网络带宽匹配，以保护重要数据和改善接收端的图象恢复质量，并提高网络带宽的利用率，经实验测试证明，此算法简单、实用、有效、且接收端的图象恢复质量比任凭网络随机丢失的情况有明显改善。     

Neuro-Fuzzy Modeling and Prediction of VBR MPEG Video Sources

The work presented in this paper intends to apply neuro-fuzzy methods for the modeling and prediction on traffic intensity of digital video sources which are coded with hybrid Motion Compensation/Differential Pulse Code Modulation/Discrete Cosine Transform (MC/DPCM/DCT) algorithm. Although current coding standards recommend constant bit rate (CBR) output by means of a smoothing buffer, the hybrid algorithm inherently produces variable bit rate (VBR) output. This paper describes the novel application of a fuzzy predictor for the purposes of modeling and prediction on video sources. The computation requirement of the fuzzy predictor and its neural network implementation are also discussed. The proposed fuzzy prediction method and its neural network version can be applied to the development of connection admission control, usage parameter control and congestion control algorithms in ATM networks.     

Hybrid multilayered perceptron networks

This paper introduces a modified multilayered perception network (MLP) called the Hybrid Multilayered Perceptron (HMLP) network to improve the performance of a MLP network. The convergence rate of the proposed network is further improved by proposing a modified version of the recursive prediction error algorithm as the training algorithm. The capability of the proposed network architecture trained using the modified recursive prediction error algorithm was demonstrated using simulated and real data sets. The results indicated that the proposed network provides a significant improvement over a standard MLP network. These additional linear input connections do not significantly increase the complexity of the MLP network since the connections are linear. In fact, by using the linear input connections, the number of hidden nodes required by the standard MLP network model can be reduced, which will also reduce computational load. The performance of the HMLP network was also compared with Radial Basis Function (RBF) and Hybrid Radial Basis Function (HRBF) networks. It was found that the proposed HMLP network was much more efficient than both RBF and HRBF networks.