Internet上实时视频流的拥塞控制策略

分析了Intemet上实时视频传输的特点．提出了基于Intemet的实时视频流的拥塞控制策略,主要包括速率控制和速率整形,速率控制主要是根据网络运行状态预测当前可用的带宽,并根据预测值调整视频速率．以达到与可用带宽匹配：速率整形则是迫使发送端以码率控制算法规定的码率发送视频流。拥塞控制技术应用于终端系统并不需要路由器和网络的Qos支持．可以最大限度地提高视频质量。     

有限带宽网络视频流传输速率控制策略研究

为促进公共视频监控领域新技术的开发和应用,立足解决工程实际问题,提出了一种有限带宽网络下视频流传输速率的控制策略。系统可以根据数据包丢失率、传输时间和时限等动态参数对网络带宽进行估测,并对实时视频的发送速率进行自适应调整,实现稳健控制,很好地解决了网络的传输带宽与视频流码率不匹配等问题。仿真实验表明,系统在降低视频时延和包丢失率、减少网络拥塞、提高带宽利用率和改善视频质量等方面效果明显。     

一种基于CDMA系统的MPEG-4视频传输速率平滑算法

该文研究了码分多址(CDMA)系统中反向链路上传输MPEG-4视频流的速率平滑算法。由于MPEG-4视频编码具有峰值速率高、速率变化频繁等特点,使得在CDMA蜂窝系统中传输变比特速率(VBR)视频有一定的难度。通过对MEPG视频在图像组(GOP)内应用速率平滑算法,结合CDMA系统物理层的传输速率匹配,可减小传输速率的峰值和变化率,节约带宽。仿真结果表明,该算法有利于提高反向链路系统稳定性,并保证MPEG-4视频的QoS要求,对于信道条件较差的用户,该算法带来的性能改进较明显。     

基于窄变带宽的实时视频传输算法

根据视频流与实时监视应用的特点,提出一种基于TCP协议的动态双缓冲与双线程视频实时传输算法。在发送方设置视频数据缓存与数据发送缓存,并分别由视频数据输入线程与视频数据发送线程负责管理;视频数据输入线程根据预设的最大等待发送时间与实时计算的网络传输速率,动态调节缓存的大小以及在网络拥塞时有选择性地丢弃视频帧;视频数据发送线程实现视频数据发送与按帧从视频数据缓存获取数据,并实时计算出网络数据传输速率。实验结果表明,本算法能最大限度地利用动态变化的网络带宽,保证视频实时发送至接收方与平稳播放,可有效地应用于窄变带宽网络环境下实时视频监视。     

基于多终端协同的高清视频多流并发自适应传输控制方法

摘要：针对高清视频在异构无线网络中以多流并发的方式进行传输,以提高传输速率,从而增强用户体验的问题,以最小化系统传输时延以及各路径间时延差为优化目标,联合考虑了视频发送端和接收端,自适应调整视频发送速率和接收端缓存大小以提高用户体验,建立了异构无线网络中视频多流并发传输的控制模型,并基于Pareto分布和P/P/1排队理论对具有自相似性和长相关性的视频流进行了研究,推导了并发传输系统的时延统计特性,并在此基础上提出了一种异构无线网络视频流自适应分流决策方法。仿真结果表明,与一般的负载均衡分流决策方法相比,提出的异构网络多流并发自适应传输控制方法在时延和分组丢失率方面都有一定的优越性。     

基于Internet的实时视频流的应用层QoS控制策略

分析了Internet上实时视频传输的特点，提出了基于Internet的实时视频流的应用层QoS控制策略，主要包括拥塞控制策略和差错控制策略以及相应的控制技术。在拥塞控制中，讨论速率控制和速率整形，速率控制主要是根据网络运行状态预测当前可用的带宽，并根据预测值调整视频速率，达到与可用带宽匹配；速率整形则是迫使发送端以码率控制算法规定的码率发送视频流。在差错控制中，则讨论了编码器差错复原、解码器错误隐藏和编码器／解码器交互的差错控制等控制策略。这些控制技术应用于终端系统并不需要路由器和网络的QoS支持，可以最大限度地提高视频质量。     

图像序列的视频流开发及网络发送的实现

Raw文件是一种原始图像,对其序列文件视频流的开发是获取图像信息的重要手段.利用DirectShow技术开发出源过滤器和发送过滤器,实现了Raw序列文件的读取和发送.文件映射和中间缓存技术的应用提高了文件读取和视频流的传输效率.     

TFRC协议友好性与平稳性改进算法研究

 本文针对TFRC(TCP-Friendly Rate Control)流与TCP流竞争带宽时的友好性问题,分析了影响TFRC协议TCP友好性的因素,通过对TFRC速率计算公式中丢包率的不同幂级项引入权重系数,增加网络拥塞严重时的发送速率,减少网络拥塞较轻时的发送速率,从而降低了网络拥塞程度对TFRC流传输速率的影响.仿真实验表明该方法对TFRC协议具有较明显改进作用,提高了TFRC流的传输平稳度和TCP友好性,从而能更有效地适应多媒体流的传输要求.     

一个基于速率控制的Internet视频流服务方案

由于视频流服务对于网络服务质量有着较高的要求,而现有的Internet所提供的是尽力而为的服务,无法保证数据的实时传输。该文设计了一个用于Internet上视频流的端到端传输方案.整个方案设计的目的是在网络本身缺乏服务质量保证的条件下尽可能达到最好的视频传输质量。根据可用带宽估计和网络信息反馈,系统对发送速率进行调整,并提供两种视频流服务:存储视频和实时视频。仿真结果表明方案的性能良好,能满足Internet视频流的需求。     

基于M值概率分布的网络视频流分类

为了改善网络视频流的细粒度分类效果,该文分析视频流传输过程中的特征变化与流分类之间的关系。根据不同类型的视频流具有不同的下行传输速率变化模式,提出一种新的基于下行速率传输的视频流分类特征--M值概率分布,并使用支持向量机(SVM)实现网络视频流的分类。实验结果表明,M值概率分布相比较于已有的常见流特征,可以更好地实现6种典型的网络视频流分类。     

TRASS: A transmission rate‐adapted streaming server in a wireless environment

The video streaming quality in a wireless communication network environment is largely affected by various network characteristics, such as a limited channel bandwidth and a variant transmission rate. The playback quality of User Equipments (UEs) may not be smooth when the service is delivered via a wireless environment. From the viewpoints of most video receivers, a smooth playback with a lower video quality may be more significant than a lagged or distorted playback with a higher video quality as the transmission rate degrades. Based on the above, we sketch an adaptation agent—Transmission‐Rate Adapted Streaming Server (TRASS), which is located between the original video server and UEs, to adaptively transform the streaming video based on the real transmission rate. In our proposed scheme, UEs would feedback their network access statuses to TRASS and then TRASS would deliver adaptive quality of video streams to UEs according to their feedbacks. The theoretical analysis and simulations using different video tracks encoded in MPEG‐4 and H.264/AVC formats show that TRASS can help wireless streaming users to get a smooth playback quality with a lower packet failure rate. With a low probability of receiving a worse quality of video, users' Quality of Experience can subsequently be raised. Copyright © 2010 John Wiley & Sons, Ltd.     

Lossless aggregation: a scheme for transmitting multiple stored VBRvideo streams over a shared communications channel without loss of imagequality

This paper introduces a new concept called lossless aggregation for the transmission of video information. It is a scheme for the delivery of variable bit-rate (VBR) video streams from a video server to a group of users over a shared channel. No data are dropped at the source during the adaptation process that reshapes the VBR video traffic to conform to the channel bit-rate characteristics. The transmission schedules of individual video streams evolve in a dynamic way that depends on their relative traffic characteristics. Receiver buffer underflow and overflow are prevented. Therefore, the data delivery process does not cause any loss of image quality. We show that very significant receiver-buffer reduction can be achieved with aggregation compared with the independent transmission of individual video streams over separate channels. Several bandwidth allocation methods for aggregation are studied extensively. The frame equalization algorithm stands out in terms of its simplicity and optimality     

Rate control for consistent visual quality of H.264/AVC encoding

In this paper, a novel rate control scheme with sliding window basic unit is proposed to achieve consistent or smooth visual quality for H.264/AVC based video streaming. A sliding window consists of a group of successive frames and moves forward by one frame each time. To make the sliding window scheme possible for real-time video streaming, the initial encoder delay inherently in a video streaming system is utilized to generate all the bits of a window in advance, so that these bits for transmission are ready before their due time. The use of initial encoder delay does not introduce any additional delay in video streaming but benefits visual quality as compared to traditional one-pass rate control algorithms of H.264/AVC. Then, a Sliding Window Buffer Checking (SWBC) algorithm is proposed for buffer control at sliding window level and it accords with traditional buffer measurement of H.264/AVC. Extensive experimental results exhibit that higher coding performance, consistent visual quality and compliant buffer constraint can be achieved by the proposed algorithm.     

Smoothing variable-bit-rate video in an internetwork

The burstiness of compressed video complicates the provisioning of network resources for emerging multimedia services. For stored video applications, the server can smooth the variable-bit-rate stream by transmitting frames into the client playback buffer in advance of each burst. Drawing on prior knowledge of the frame lengths and client buffer size, such bandwidth-smoothing techniques can minimize the peak and variability of the rate requirements while avoiding underflow and overflow of the playback buffer. However, in an internetworking environment, a single service provider typically does not control the entire path from the stored-video server to the client buffer. This paper presents efficient techniques for transmitting variable-bit-rate video across a portion of the route, from an ingress node to an egress node. We develop efficient techniques for minimizing the network bandwidth requirements by characterizing how the peak transmission rate varies as a function of the playback delay and the buffer allocation at the two nodes. We present an efficient algorithm for minimizing both the playback delay and the buffer allocation, subject to a constraint on the peak transmission rate. We then describe how to compute an optimal transmission schedule for a sequence of nodes by solving a collection of independent single-link problems, and show that the optimal resource allocation places all buffers at the ingress and egress nodes. Experiments with motion-JPEG and MPEG traces show the interplay between buffer space, playback delay, and bandwidth requirements for a collection of full-length video traces     

Optimal video stream multiplexing through linear programming

This paper presents a new optimal multiplexing scheme for compressed video streams based on their individual e-PCRTT transmission schedules. A linear programming algorithm is proffered, which takes into account the different constraints of each client. The algorithm simultaneously finds the optimum total multiplexed and individual stream schedules that minimize the peak transmission rate. Since the problem is formulated as a linear program it is bounded in polynomial time. It is shown that the algorithm succeeds in obtaining maximum bandwidth utilization with Quality of Service (QoS) guarantees. Simulation results using 10 real MPEG-1 video sequences are presented. The optimal multiplexing linear programming results are compared to the e-PCRTT and Join-the-Shortest-Queue (JSQ) procedures in terms of peak transmission bandwidth, P-loss performance and standard deviation. For several client buffer sizes, the rate obtained by our LP solution when compared to a previous e-PCRTT and JSQ methods resulted in reductions of 47% and 56%, respectively. This implies for a fixed rate problem that the proposed scheme can allow an increase in the number of simultaneously served video streams.     

基于无线视频服务器自适应带宽算法

针对无线网络上行带宽有限的情况,提出了无线视频传输带宽的自适应算法。采用双卡发送采集的视频流数据,这样大大增加了无线视频传输带宽。解决了公共无线网络带宽资源有限的问题。使得无线视频传输码率能够达到500～900 kbit/s。在接收端采取双缓冲区的设计,在客户端能够得到清晰、流畅的视频图像。从而解决了无线视频传输和带宽不足的问题。     

基于Android的视频流自适应算法设计

随着网络的快速发展,对高质量视频的实时传输提出了更高的要求,然而由于智能手机处理能力低、内存小等硬件配置因素,使得嵌入式媒体播放器中的视频数据无法自适应网络状况,最终导致视频数据在传输过程中大量丢失,降低接收到的视频图像质量。在此提出基于Android的视频流自适应算法,该算法可动态探测网络带宽,自动适应网络拥塞状况,制定平滑的数据传输带宽,缓解网络拥塞．根据传输带宽控制视频编码和视频传输速率,提高视频传输质量。     

基于多模式匹配的网络视频流识别与分类算法

快速发现网络中的视频流是进行网络视频监督及管理的前提与基础。本文通过分析网络视频流数据包的特征,提出了一种基于多模式匹配思想的网络视频流快速发现与分类算法,该算法利用不同视频流的特征建立匹配机,只需对网络数据包进行一次不完全扫描,就可以判断出数据包中是否含有视频流及类型。实验结果表明,与普通的协议解析方法相比,在满足准确性的前提下,所提算法具有更好的时间性能。     

A neural network-based video bit-rate control algorithm for variable bit-rate applications of versatile video coding standard

Versatile video coding is a new video coding standard that has more capabilities and higher coding efficiency compared with its predecessor. Practical video storage and transmission applications face constrained buffer size and available bandwidth. It is necessary to design the appropriate rate control algorithm to overcome such challenges. In this paper, the non-linear relationship between consumed bits, buffer size, and quantization parameter is estimated by taking the advantages of artificial neural networks, and a rate control algorithm is developed for real-time variable bit rate applications of the versatile video coding standard. The proposed rate control algorithm performs the control action in only one step that results in faster control action. The experimental results show that the proposed algorithm controls the bit-rate as well as the buffer state. Also, the rate–distortion analysis shows that the well-known $\lambda$-domain algorithm has only 2.7% bit-rate reduction in comparison with the proposed method.     

An analytic study of a scalable video buffer

In this contribution, we investigate the performance of the output buffer of an ‘on-demand’ video streaming server. The server maintains a local database of stored video clips and movies which can be streamed to the users upon request. We assume that the stored video is encoded in a scalable way, which means that the data streams contain a base layer ensuring a minimum of guaranteed quality and a stack of additional enhancement layers progressively improving the quality of the video. For the purpose of performance analysis, we assume that a video stream is split up in logical units called frames. Every frame consists of a number of packets, each containing information of one layer only. When the output buffer gets congested, one may choose to drop the transmission of some of the layers in a frame, thus reducing the frame transmission time and expediting the restoration of the buffer size to normal levels. A discrete-time finite capacity queueing model with buffer size dependent transmission times is proposed. Using a probability generating function approach, we focus on the characteristics of idle and busy periods. We obtain performance measures such as the frame loss ratio and the average frame transmission time. The latter measure relates to the quality of the video stream. We conclude with some numerical examples, including a realistic case study.