自相似VBR视频源业务流的建模和仿真

该文在对实际ＶＢＲ ＭＰＥＧ视频源统计特性分析的基础上,参照分形高斯噪声自相似（Ｆｒａｃｔｉｏｎａｌ Ｇａｕｓｓｉａｎ Ｎｏｉｓｅ Ｓｅｌｆ－Ｓｉｍｉｌａｒ）模型产生方法,实现了对ＡＴＭ网络中最主要业务流－ＶＢＲ视频源流的建模,提出了改进方法,使得对实际源的仿真不仅考虑到了长期相关性,同时也兼顾到了短期相关性。仿真结果表明,经改进的自相似ＶＲＢ视频源模型是一种较理想的模型。     

基于小波支持向量机的VBR视频流量预测

：VBR视频流量具有时变性、突发性和非线性等变化特点,为了提高VBR视频流量的预测精度,提出一种小波支持向量机的VBR视频流量预测模型(WSVM)。首先对VBR视频流量时间序列进行相空间重构,然后将其输入到小波支持向量机进行学习,建立VBR视频流量预测模型,最后采用仿真实验对模型性能进行测试,并与支持向量机、小波神经网络进行对比。仿真结果表明,相对于其它预测模型,WSVM模型提高了VBR视频流量预测精度,能够更加准确反映VBR视频流量的复杂变化规律。     

基于小波支持向量机的VBR视频流量预测模型

针对VBR视频流量的时变性、突发性和非线性等特点,提出一种基于小波支持向量机的VBR视频流量预测模型(WSVM)。首先对VBR视频流量时间序列进行相空间重构,然后将其输入到小波支持向量机进行学习,建立VBR视频流量预测模型,最后采用仿真实验对模型性能进行测试。结果表明,相对于对比模型,WSVM提高了VBR视频流量预测精度,更加准确地描述了VBR视频流量的复杂变化特点。     

VBR MPEG-2业务统计复用特性的研究

VBR MPEG－2业务是ATM网络中的重要视频业务类型。本文建立了两个流体流视频复用模型，对其信元丢失率和传输延时特性进行了定性分析，得到了一些重要结论。通过对VBR MPEG－2业务进行复用仿真，验证了这些结论，并对业务源参数、复用缓冲器容量、业务强度与信元丢失率、传输延时特性之间的关系进行了分析。对ATM交换机和复用器的设计与性能分析具有一定指导意义。     

VBR视频流多重分形建模

该文在小波域多重分形基础上,研究了基于分布、点集(PM)分布的多重分形小波模型(MWM)的性能,并提出了一种具有更好的逼近性能的混合PM-分布形式;同时,针对VBR视频流的I,P,B帧周期分布特性,充分利用异种帧相关性,建立了考虑帧间相关性的混合多重分形小波VBR视频流量模型CMWM(Composite MWM)。仿真试验表明,与传统的短相关和长相关模型相比,具有多重分形特性的CMWM能更加精确地描述MPEG视频业务的统计特性和排队性能。     

一种基于扩展自相似过程的VBR视频业务新模型

本文在扩展自相似过程的基础上 ,提出了一种简单的视频业务新模型。该模型的边缘分布近似Gamma分布 ,且其具有长或短的相关性。在许多时间尺度上 ,这些特性可以很好地匹配众多实际变比特率视频业务的一、二阶统计特征。仿真实验中 ,通过利用该模型模拟实际视频信号 ,我们证明它也能很好地反映实际视频业务的排队性能     

VBR视频流量的小波包分解及其长时预测

长时预测是VBR视频流量预测领域中的难点问题.针对其时变、非线性以及长相关性等特点,提出一种多尺度分解的VBR视频业务的特征提取方法.选择具有任意多分辨分解特性的小波包,对其进行空间划分并求解适合视频信号特征提取的最优分解基.基于最优基对视频信号进行快速多尺度分解,得到了各级节点的小波系数矩阵,建立了基于最小二乘支持向量机与最小均方的小波系数预测方法.最后,根据预测小波系数,进一步提出了基于小波系数逆变换的视频流量长时预测方法.仿真结果验证了此算法的有效性.     

VBR视频在IPTV点播业务中的应用

通过对VBR视频流量进行工程建模,结合IPTV用户点播时间间隔分析聚合VBR视频流量特性,研究表明在兼容现有终端和平台系统的情况下,即使不采用任何视频平滑处理,在IPTV点播业务中通过应用大规模VBR视频流的统计随机特性进行自我平均(self-average)也可获得30%~50%的统计增益,并通过大规模现场试验验证了VBR视频自平均特性在IPTV点播业务中的可行性和有效性。     

MPEG—2视频业务的两种自回归模型的对比

为了实现多媒体节目流在IP网上的实时播放,因特网工程任务组（IETF）为MPEG－2码流的分割及实时传输制定了相关的协议。根据此协议对MOPEG VBR码流进行分割后,MPEG的三种类型型帧的自相关结构都表现出短时相关性,因此,采用AR（2）模型对三种类型的帧的大小进行了模拟,并且与AR（1）模型进行了对比。结果表明,AR（2）比AR（1）模型能够更好地反映视频源的统计特性。     

突发业务流的TES建模方法

高速通信网络存在大量诸如可变速率(VBR)视频这类具有突发性的业务流。突发性,在数学上主要通过业务流的到达时间间隔的边缘概率分布和自相关函数来描述。TES(Transform-Expand-Sample)是一种建模静态随机过程的非参数化技术,能准确匹配边缘概率分布并很好地近似自相关函数。本文简要介绍了TES方法的基本原理,再详细讨论突发业务流的TES建模及其软件实现。对MPEG视频业务的建模的仿真结果表明,TES模型能够很好地表征网络业务流的突发性。     

Modeling MPEG Coded Video Traffic by Markov-Modulated Self-Similar Processes

Markov modulated self-similar processes are proposed to model MPEG video sequences that can capture the LRD (Long Range Dependency) characteristics of video ACF (Auto-Correlation Function). The basic idea is to decompose an MPEG compressed video sequence into three parts according to different motion/content complexity such that each part can individually be described by a self-similar process. Beta distribution is used to characterize the marginal cumulative distribution (CDF) of the self-similar processes. To model the whole data set, Markov chain is used to govern the transitions among these three self-similar processes. In addition to the analytical derivation, initial simulations have demonstrated that our new model can capture the LRD of ACF and the marginal CDF very well. Network cell loss rate using our proposed synthesized traffic is found to be comparable with that using empirical data as the source traffic.     

Study of the impact of MPEG-1 correlations on video-sourcesstatistical multiplexing

Variable bit-rate (VBR) video is expected to become increasingly important with the large scale deployment of broadband-integrated services networks (B-ISDNs). While the modeling of VBR video sources has received significant attention, there is no widely accepted model which lends itself to mathematical analysis. Furthermore, new video compression standards are emerging, such as the MPEG family. A detailed statistical analysis of a long sample of a movie encoded with an MPEG-1 algorithm highlights that traffic generated by an MPEG-1 encoder has both a high degree of burstiness (peak/average ratio greater than five) and a strong long-term correlation (positive correlation lasts for ten/twenty minutes). In this paper, we propose and analyze a Markov model which captures both the burstiness and the temporal dependencies of MPEG traffic. Furthermore, we show that our model is a flexible traffic generator which is suitable for studying statistical multiplexing issues. Specifically, we study both the multiplexing of a VBR video source with low priority traffic and the multiplexing of several VBR video sources. The results obtained show that the long-term correlation significantly affects the tail of the delay distribution even for lightly loaded networks. The presence of a long range dependence in the MPEG traffic significantly reduces the gain in terms of network utilization which can be achieved with statistical multiplexing of i.i.d. sources     

考虑异种帧相关性的VBR MPEG视频源混合回归模型

ＭＰＥＧ作为一种国际动态图像压缩标准,其越来越广泛。为在通信网络上有效地传输和控制ＭＰＥＧ可变经特率（ＶＢＲ）数据流,第一个关键问题就是如何建立它的统计模型,目前已有的视频源模型都没有考虑不同类型帧之间的相关性,并不能很好地模拟ＶＢＲＭＰＥＧ视频源。本文首次提出了一咋处世划种帧相关性的ＶＢＲＭＰＥＧ视频源统计模型,混合回归（ＣＲ）模型,及其参数估计算法,实验结果表明,和传统的自回归（ＡＲ）模型相比     

A new approach to long‐range dependence in variable bit rate video traffic

Recently it has been observed that variable bit rate (VBR) video traffic displays long‐range dependence, which suggests that traditional Markovian models may not be suitable for performance evaluation of telecommunications networks carrying this traffic. Inspection of the bit rate profile of VBR video traffic suggests that shifting level processes might be more appropriate for this task. In this paper we show that a particular class of these processes matches the autocorrelation and bit rate distribution of real VBR video traffic, including exhibiting long‐range dependent behaviour. This revised version was published online in June 2006 with corrections to the Cover Date.     

SIMULATION AND MODELLING OF VARIABLE BIT RATE MPEG VIDEO TRANSMISSION OVER ATM NETWORKS

This paper proposes an efficient transmission mechanism based on frame spreading, for variable bit rate (VBR) MPEG compressed video, through an asynchronous transfer mode (ATM) multiplexer, such as a cable head-end. We implement a priority scheme in a software MPEG encoder which produces proportionate traffic in both (i.e. high and low) priority partitions for all three types of video frames used in MPEG, i.e. intraframe (I), predicted (P) and bidirectionally interpolated (B). Furthermore, we simulate an ATM multiplexing scheme with a pushout buffer mechanism providing priority scheduling at the multiplexer for the two video partitions. We load the multiplexer with VBR MPEG traffic and collect performance statistics such as the cell loss ratios for various frame spreading scenarios. In order to study the transmission mechanisms via simulation, we develop two statistical models, using the transform-expand-sample technique (TES) for VBR MPEG video with two levels of priority. The first model is matched with the empirical histogram and autocorrelation function of each frame type (I, P and B). The second model is created with the assumption of a gamma distribution for the number of bits in each frame type. We conduct experiments using both models and compare the results.     

VBR Video Source Characterization and a Practical Hierarchical Model

There are many ways to build up traffic models for VBR video sources. A frequently applied methodology is to use mathematical analysis based on realistic assumptions to set up a source model that generates traffic according to a stochastic process. In this case, the critical issue is the validation of the synthetic trace by comparing statistics to results obtained from measurements on the real source. In this paper, we choose a different and more practical approach to model the behavior of the real traffic source. Our model building philosophy is that we analyze and understand what happens with the video information on its way from the ingress to the multimedia terminal to the egress of the network card. Throughout this journey the information is processed by several mechanisms and we build an empirical model step by step based on our measurement-based observations. Besides understanding the traffic generation procedure, statistical analysis of VBR traffic traces captured from a number of video sequences was also carried out in several scenarios. Using the knowledge of encoding, encapsulation and scheduling processes and results of the trace analysis, a hierarchical source model is set up for modeling the multimedia terminal. Thereby our model imitates the generation of video frames and the inner working of each level of protocol hierarchy and tries to reproduce the complex behavior of the real source. We use the leaky bucket analysis for verification of the model in order to capture directly the behavior of the traffic in a queue.     

An approximation for the loss probability in a multiserver queue fed by a shifting level process

A shifting level (SL) process is useful to traffic modeling because it is very easy to match the stationary distribution and autocorrelation function of the SL process with those of measured real traffics. Especially, SL processes have been used to traffic modeling for VBR video traffics reflecting the long range dependence and the scene structure. We give an approximation for the loss probability in a multiserver queue fed by a SL process. Numerical examples show that our approximation is very accurate.     

Implementation of SDTV Video Encoder with Real-Time Constant and Variable Bit-Rate Control

The digital standard definition television (SDTV) encoder is a very important part of the digital TV broadcast chain. Most real-time MPEG-2 encoders are designed to perform in a constant bit-rate (CBR) mode. But an even better compressed stream can be created by employing a variable bit-rate (VBR) encoding algorithm. VBR can be exploited as a means of achieving statistical multiplexing for digital broadcast satellites. This paper suggests an implementation procedure of an SDTV video encoder and proposes a novel VBR bit-allocation strategy that could be implemented in this encoder system. First, using a rate-quantization model and rate-quantization perceptual model, a real-time VBR bit-allocation strategy is deduced. In this strategy, more (or fewer) bits are allocated to "difficult-to-encode" (or "easy-to-encode") groups of pictures (GOPs), which are distinguished according to the estimated encoding complexity of the GOPs. After allocating an appropriate number of bits to each GOP by using this VBR bit-allocation strategy, we use a CBR rate control algorithm to allocate a number of bits and select a quantization scaler for each picture of a GOP. Then smooth visual quality is achieved not only in a GOP but also in the whole video sequence. Second, the system implementation of an SDTV video encoder including a video input module, a video encoding module, a system control and rate control module (SCRCM), and a PES packetizing module is described. We also discuss in detail how to implement our real-time VBR bit-allocation strategy in the SCRCM. Finally, experimental results demonstrate that our proposed VBR encoder displays a better performance than the CBR encoder.