一种多路传输可伸缩视频流的分组调度算法

由于无线网络带宽不足,不能满足高质量视频的传输要求,终端用户往往会遭受频繁的播放中断.为了解决上述问题,一种可能的办法是利用终端的多模特性并发地多路传输视频流.多路传输视频流的关键技术之一是分组调度算法,即将视频分组分配到适合的接口进行传输.本文研究了一种多路传输可伸缩编码视频流下基于质量驱动的分组调度算法.为了最大限度地提升接收端的视频质量,该分组调度算法考虑了接入网络的特性以及视频帧的特征.在本文中,视频数据包调度的问题建模为一个受限多重背包问题,而这个问题是已知为NP-hard的.然后,提出了一种分组调度算法,将视频分组调度到合适的接入网进行传输.在NS-2仿真软件中使用真实的视频trace文件去验证该算法利用多模终端传输可伸缩编码视频的性能.仿真结果表明,分组调度算法在PSNR上优于速率控制算法和传统的round-robin算法.     

WiMAX网络中基于优先级的视频分组调度算法

无线视频传输是网络传输的研究热点,在WiMAX网络中,实时轮询业务(rtPS)的典型应用是实时视频传输,当前使用较多的是先进先出(FIFO)和最早到达期限数据优先(EDF)队列调度算法,其中EDF算法多用于多业务之间的资源分配,而非单个业务流队列的出对调度。在视频优先级以及WiMAX网络为单个视频流分配带宽限定的条件下进行调度算法的研究,以期待在带宽有限的情况下得到更高的视频服务质量。     

Content-Aware Playout and Packet Scheduling for Video Streaming Over Wireless Links

Media streaming over wireless links is a challenging problem due to both the unreliable, time-varying nature of the wireless channel and the stringent delivery requirements of media traffic. In this paper, we use joint control of packet scheduling at the transmitter and content-aware playout at the receiver, so as to maximize the quality of media streaming over a wireless link. Our contributions are twofold. First, we formulate and study the problem of joint scheduling and playout control in the framework of Markov decision processes. Second, we propose a novel content-aware adaptive playout control, that takes into account the content of a video sequence, and in particular the motion characteristics of different scenes. We find that the joint scheduling and playout control can significantly improve the quality of the received video, at the expense of only a small amount of playout slowdown. Furthermore, the content-aware adaptive playout places the slowdown preferentially in the low-motion scenes, where its perceived effect is lower.      

大规模客户端视频流带宽调度

视频流服务的迅猛发展, 大规模用户共享带宽链路的场景不断增多. 现存的DASH视频流采用的ABR算法多用于提高单客户端用户的体验质量(quality of experience, QoE), 还有一些算法仅针对数个客户端的情况. 本文提出一种应用于大规模客户端场景的带宽调度算法, 通过聚类算法减小调度规模, 再将带宽分...     

一种按需分配的多路径传输分组调度算法

利用多路径传输协议,多宿主主机可以通过多条路径并行传输数据,从而有效提高系统的吞吐率和鲁棒性.但是由于不同路径在带宽、延迟和丢包率等方面存在差异,接收端必须缓存大量乱序到达的分组.数学分析表明,减少接收端的缓存开销有两条途径:一是最小化每条路径的发送队列中积压分组的数量,二是降低分组发送速率.由前者,提出依据每条路径的空闲发送窗口大小进行分组调度的算法SOD(Scheduling On Demand);由后者,提出利用窗口通告机制限制分组发送速率的流控方法.模拟实验结果表明:与现有算法相比,SOD的缓存开销最小;在接收端进行流控限制的情况下,SOD的吞吐率最大,并且在不同实验场景中性能表现稳定.     

A Demand Based Packet Scheduling Algorithm for Multipath Transfer

利用多路径传输协议,多宿主主机可以通过多条路径并行传输数据,从而有效提高系统的吞吐率和鲁棒性.但是由于不同路径在带宽、延迟和丢包率等方面存在差异,接收端必须缓存大量乱序到达的分组.数学分析表明,减少接收端的缓存开销有两条途径:一是最小化每条路径的发送队列中积压分组的数量,二是降低分组发送速率.由前者,提出依据每条路径的空闲发送窗口大小进行分组调度的算法SOD(Scheduling On Demand);由后者,提出利用窗口通告机制限制分组发送速率的流控方法.模拟实验结果表明:与现有算法相比,SOD的缓存开销最小;在接收端进行流控限制的情况下,SOD的吞吐率最大,并且在不同实验场景中性能表现稳定.     

一种嵌入视频流的丢包自测量方法

现有的丢包主动测量方法是通过探测流的丢包信息去推测网络的丢包特性,进而推测特定应用流的丢包,测量结果不能准确获知某一给定应用流的丢包情况.由于丢包通常属于短时间、小概率事件,要更加准确地测量丢包就意味着需延长测量时间,或者提高探测流的发送速率以及时发现丢包,这将不可避免地增加网络的额外负载.分析了不同类型帧损伤的影响,并以MPEG-4,H264 视频为研究对象,通过对其码流结构特点及RTP 封装策略的分析,提出一种将测量信息嵌入到视频用户数据域(User_Data)的丢包测量方法PLBU(packet loss measurement based on User_Data).该方法利用视频码流信息完成对丢包的探测,不影响视频的正常播放,不需要注入新的探测流,极大地降低了因测量而引入的额外负载.NIST Net 及Planetlab 等实验结果表明,该算法不仅丢包测量准确性高,且可提供丢包所属视频帧类型等信息,如视频中I,P,B 帧的数据包丢失的情况.借助该测量方法,服务提供商可评测网络视频流丢包,并分析视频体验质量(QoE)变化情况,且不受视频流在网络传输中的优先级影响.     

Noncausal Error Control for Video Streaming Over Wireless Packet Networks

Video streaming systems usually employ a reasonably large receiver buffer to deal with jitter. The existence of such a buffer allows us to implement noncausal algorithms for video processing at the receiver. In this paper, we describe an error control scheme that takes advantage of this fact, and employs a non-causal error-concealment algorithm. We use the knowledge of the packet-loss realization for the previously transmitted data to adjust the transmission strategy for the future data, knowing that this future data will be used to conceal the data in the previously lost packets. We demonstrate that such a strategy can be several times more energy efficient than ARQ     

Efficient Streaming Packet Video Over Differentiated Services Networks

We investigate streaming video over Differentiated Services (Diffserv) networks that can provide a number of aggregated traffic classes with increasing quality guarantee. We propose a method to measure the loss impact of a video packet on the quality of the decoded video images. We show how the optimal Quality-of-Service (QoS) mapping from the video packets into a set of traffic classes depends on the loss rates of the classes and the pricing model, and we develop an algorithm to accurately find the optimal QoS mapping. The performance of our algorithm is evaluated through computer simulations and compares favorably to an existing algorithm.     

层次编码流媒体发送调度的研究

文章针对层次编码流媒体数据在Internet上进行传输的问题,研究服务端包发送调度技术。根据发送缓冲区中层次编码流媒体数据包之间存在的多重依赖关系和传输时间限制,提出了服务端发送调度的马尔科夫模型,在该模型的基础上,用值迭代法实现一个最优的发送策略。该策略能够在带宽受限的条件下,保证重要性较高的数据包优先发送出去。通过实验证明,与顺序发送方法比较,该调度算法能够在客户端获得更好的播放质量。     

Fine-Granularity Transmission Distortion Modeling for Video Packet Scheduling Over Mesh Networks

Packet scheduling is a critical component in multi-session video streaming over mesh networks. Different video packets have different levels of contribution to the overall video presentation quality at the receiver side. In this work, we develop a fine-granularity transmission distortion model for the encoder to predict the quality degradation of decoded videos caused by lost video packets. Based on this packet-level transmission distortion model, we propose a content-and-deadline-aware scheduling (CDAS) scheme for multi-session video streaming over multi-hop mesh networks, where content priority, queuing delays, and dynamic network transmission conditions are jointly considered for each video packet. Our extensive experimental results demonstrate that the proposed transmission distortion model and the CDAS scheme significantly improve the performance of multi-session video streaming over mesh networks.     

Video Streaming for Mobile Video Surveillance

Mobile video surveillance represents a new paradigm that encompasses, on the one side, ubiquitous video acquisition and, on the other side, ubiquitous video processing and viewing, addressing both computer-based and human-based surveillance. To this aim, systems must provide efficient video streaming with low latency and low frame skipping, even over limited bandwidth networks. This work presents MoSES (MObile Streaming for vidEo Surveillance), an effective system for mobile video surveillance for both PC and PDA clients; it relies over H.264/AVC video coding and GPRS/EDGE-GPRS network. Adaptive control algorithms are employed to achieve the best tradeoff between low latency and good video fluidity. MoSES provides a good-quality video streaming that is used as input to computer-based video surveillance applications for people segmentation and tracking. In this paper new and general-purpose methodologies for streaming performance evaluation are also proposed and used to compare MoSES with existing solutions in terms of different parameters (latency, image quality, video fluidity, and frame losses), as well as in terms of performance in people segmentation and tracking.      

率失真优化的无线多跳网络多路径选择算法

随着无线网络技术的发展,基于无线多跳网的视频通信在智能交通、灾难应急和军事指挥等多个领域得到越来越广泛的应用.但是,如何保证无线视频的传输质量,是亟待解决的一个关键问题.已有多路径视频传输研究忽略了信道变化和路径间干扰.针对该问题,提出一种基于率失真预测的多路径选择优化算法.该算法不仅分析了网络拥塞对传输质量的影响,而...     

Delay-Distortion Optimization for Content-Adaptive Video Streaming

We propose a new pre-roll delay-distortion optimization (DDO) framework that allows determination of the minimum pre-roll delay and distortion while ensuring continuous playback for on-demand content-adaptive video streaming over limited bitrate networks. The input video is first divided into temporal segments, which are assigned a relevance weight and a maximum distortion level, called relevance-distortion policy, which may be specified by the user. The system then encodes the input video according to the specified relevance-distortion policy, whereby the optimal spatial and temporal resolutions and quantization parameters, also called encoding parameters, are selected for each temporal segment. The optimal encoding parameters are computed using a novel, multi-objective optimization formulation, where a relevance weighted distortion measure and pre-roll delay are jointly minimized under maximum allowable buffer size, continuous playback, and maximum allowable distortion constraints. The performance of the system has been demonstrated for on-demand streaming of soccer videos with substantial improvement in the weighted distortion without any increase in pre-roll delay over a very low-bitrate network using AVC/H.264 encoding     

Service Sharing for Streaming Video Multicast

In a general context, the sharing of intermediate service results among different processes is seldom feasible because parameters are often different and there may be transactional and side effects. However, in a streaming video multicast environment, a large number of users often request various similar processing on the same stream. Therefore, service sharing is feasible, with a large potential of savings in processing cost. In this paper, we study the problem of determining the service invocation orders for multiple service composition requests in a streaming video multicast with the aim of maximizing the service sharing. We first formally define the problem. After proving the problem is NP-Complete, we develop an optimal algorithm for the base case of two requests. Then for the general case, we develop two heuristic algorithms, namely, a global greedy algorithm and a local greedy algorithm using the optimal algorithm for the base case as the building block. The global greedy algorithm is designed for a system where the existing service composition requests can be recomposed with the arrival of a new request. The local greedy algorithm can be used in a system where the existing service composition requests do not change their service composition solutions with the arrival of a new request. We prove that the global greedy algorithm is a 2-approximation algorithm in terms of maximizing service sharing. Simulation results show that the greedy algorithms can save more service costs compared with a naive algorithm, and are effective compared with the cost lower bound.      

Investigating the Scheduling Sensitivity of P2P Video Streaming: An Experimental Study

Peer-to-peer (P2P) technology has recently been employed to deliver large scale video multicast services on the Internet. Considerable efforts have been made by both academia and industry on P2P streaming design. While academia mostly focus on exploring design space to approach the theoretical performance bounds, our recent measurement study on several commercial P2P streaming systems indicates that they are able to deliver good user quality of experience with seemingly simple designs. One intriguing question remains: how elaborate should a good P2P video streaming design be? Towards answering this question, we developed and implemented several representative P2P streaming designs, ranging from theoretically proved optimal designs to straightforward “naive” designs. Through an extensive comparison study on PlanetLab, we unveil several key factors contributing to the successes of simple P2P streaming designs, including system resource index, server capacity and chunk scheduling rule, peer download buffering and peering degree. We also identify regions where naive designs are inadequate and more elaborate designs can improve things considerably. Our study not only brings us better understandings and more insights into the operation of existing systems, it also sheds lights on the design of future systems that can achieve a good balance between the performance and the complexity.      

A Packet Selection Algorithm for Adaptive Transmission of Smoothed Video over a Wireless Channel

This paper discusses techniques for transmitting smoothed video more efficiently over a wireless network. The fluctuation of wireless channel conditions can add a significant amount of delay to video packets and cause them to miss their play-out time. If a video is smoothed, it is possible to selectively deliver packets delayed at the base-station to reduce the impact of the missing packets on video quality. In this paper, we present a simple yet effective packet selection algorithm which accomplishes this goal. This algorithm determines whether to transmit a packet based on channel conditions as well as the likelihood that higher priority layers in the rest of the video will be delivered on time. We introduce the concept of quality index to measure the performance of the algorithm. Results from trace-driven simulations show that the performance of the algorithm is close to optimal under a wide variety of channel conditions when the threshold is set between 0.7 and 0.9.     

一个融合组播流媒体系统

文章对目前网络中IP 组播流媒体存在组播孤岛和不同接入带宽用户群组播数据不能共享等问题,提出了一种新的流媒体融合组播覆盖网络,研究通过P2P 互联不同IP 组播区,实现组播数据共享。每一个IP 组播区内有一个IP 组播源(IP-SM)和一到多个P2P 组播源(P2P-SM),所有的IP-SM 和P2P-SM 组成一个融合组播树,将不同的IP 组播区互联。IP 组播区内采用网络层组播技术,组播区之间采用应用层组播技术,实现不同组播模式的融合,使流媒体系统具有扩展性和网络适应能力。     

FGS视频均等质量流化算法

细粒度扩展编码(FGS:Fine-Granularity-Scalability)由于具有很强的灵活性和较好的视频流化性能已经被MPEG-4和H.26L等标准所采用。论文在相关研究的基础上,采用了基于滑动窗口的算法来进行FGS视频的均等质量流化。该算法通过FGS的失真模型,使用二分法对当前窗口中的所有帧进行速率分配。实验表明,该算法可以较好地实现速率的优化分配,使连续图像质量的变化更加平滑。     

Distributed Collaboration for Enhanced Sender-Driven Video Streaming

We propose a sender-driven system for adaptive streaming from multiple servers to a single receiver over separate network paths. The servers employ information in receiver feedbacks to estimate the available bandwidth on the paths and then compute appropriate transmission schedules for streaming media packets to the receiver based on the bandwidth estimates. An optimization framework is proposed that enables the senders to compute their transmission schedules in a distributed way, and yet to dynamically coordinate them over time such that the resulting video quality at the receiver is maximized. To reduce the computational complexity of the optimization framework an alternative technique based on packet classification is proposed. The substantial reduction in online complexity due to the resulting packet partitioning makes the technique suitable for practical implementations of adaptive and efficient distributed streaming systems. Simulations with Internet network traces demonstrate that the proposed solution adapts effectively to bandwidth variations and packet loss. They show that the proposed streaming framework provides superior performance over a conventional distortion-agnostic scheme that performs proportional packet scheduling on the network paths according to their respective bandwidth values.