Interlayer Jitter Index for the Transmission of Layered Video Stream over the Internet

A novel scheme of dynamic bandwidth allocation and buffer dimensioning based on the video playback tunnel and the jitter_index tunnel is proposed to guarantee the synchronization between the basic layer video stream and the enhancement layer video streams in the transmission of layered video streams over the Internet. The performance of the proposed scheme is evaluated using a set of real-life video traces with the focus on the effects of bandwidth, traffic burstiness and network traffic loading on the statistics of jitter_index between the basic layer and enhancement layers. The numerical results show that the proposed dynamic bandwidth allocation and buffer dimensioning scheme is able to significantly reduce the effect of interlayer jitters in the transmission of multiple layer-coded video streams over the Internet.     

Dual-plan bandwidth smoothing for layer-encoded video

Traditional bandwidth smoothing techniques can be naturally supported by the renegotiated constant bit rate (RCBR) service model, but renegotiation failure in RCBR may cause buffer underflow and interrupt the playback of video. To address this concern, a novel dual-plan bandwidth smoothing (DBS) scheme is proposed in this paper by taking advantage of the SNR scalability of layer-encoded video. Upon renegotiation failure, the proposed scheme can adaptively discard certain enhancement layers to guarantee continuous video playback at the original frame rate. Experiments are carried out to demonstrate the validity of the proposed scheme. The impacts of renegotiation interval, granularity of enhancement layers, and playback buffer size on resulted video quality are also studied. From the simulation results, it is shown that the performance of the RCBR-based DBS scheme can be improved by 1) reducing the minimum time gap of renegotiation interval; 2) employing multilayer video encoding with finer granularity; and/or 3) increasing the playback buffer size.     

Adaptive bandwidth allocation based on playback tunnel to support video on demand service over ATM networks

This paper focuses on adaptive bandwidth allocation (ABA) for transporting pre-stored VBR compressed video data across networks in support of video-on-demand (VoD) service. Two key issues are addressed. Firstly, a simplified dynamic programming method based on playback tunnel is proposed to predict the bandwidth which can be dynamically allocated for transporting video segment to guarantee that the playback buffer neither underflows nor overflows. Secondly, ABA schemes with different criteria including middle-tunnel ABA (MT-ABA) and reduced-bandwidth-variability ABA (RBV-ABA) are investigated. The proposed ABA schemes are evaluated by a set of real-life MPEG video traces. The obtained results show that the RBV-ABA scheme outperforms MT-ABA scheme in terms of peak rate, traffic burstiness and bandwidth variability. On the other hand, the MT-ABA scheme is more significant for avoiding the playback buffer overflow or underflow than that of RBV-ABA.     

易错视频传输中基于带宽-失真代价最小化准则的部分重传算法

针对视频传输系统主要关注的两个因素:传输所用的总体带宽和终端最终的解码失真,提出带宽-失真(B D)代价函数的概念,给出B-D关系定理及其证明.利用视频数据本身存在的时空相关的特点,进一步提出了基于最小化B D代价的部分重传机制.实验结果及分析表明,相对于尽力而为ARQ机制,所提出的算法有如下几个特点:(1)在保持终端接收质量基本不变的前提下,能有效减少带宽(可达20%以上);(2)在低比特率情形下性能比高比特率下的性能要好,所以更适合于低比特应用;(3)对运动平缓和纹理平滑的视频序列更为有效.     

基于视点预测的全景视频码率自适应策略

为解决全景视频传输中存在的视频卡顿多、用户体验质量（quality of experience,QoE）低等问题,研究当前主流的视点自适应传输方案,提出一种基于视点预测的码率自适应策略（VPBAS）。首先,构建了一种基于长短期记忆网络和全卷积网络的视点预测模型,模型将视点数据和视频显著性信息进行特征融合,实现不同模态数据的相互补充和修正,提高视点预测的准确率;然后,客户端采用随机森林算法预测当前的可用带宽,并根据视点预测结果和可用带宽信息为视频分块选择码率。最后,客户端把选择的码率信息定期发送给服务器,服务器根据反馈的信息向客户端推送最佳码率的全景视频流,这种交互过程在视频播放期间不断地重复,直至客户端观看完毕。实验结果表明,与现有传输方案相比,VPBAS能有效提高带宽受限情况下的视频观看体验。     

Optimal proxy cache allocation for efficient streaming media distribution

We address the problem of efficiently streaming a set of heterogeneous videos from a remote server through a proxy to multiple asynchronous clients so that they can experience playback with low startup delays. We determine the optimal proxy prefix cache allocation to the videos that minimizes the aggregate network bandwidth cost. We integrate proxy caching with traditional server-based reactive transmission schemes such as hatching, patching and stream merging to develop a set of proxy-assisted delivery schemes. We quantitatively explore the impact of the choice of transmission scheme, cache allocation policy, proxy cache size, and availability of unicast versus multicast capability, on the resulting transmission cost. Our evaluations show that even a relatively small prefix cache (10%-20% of the video repository) is sufficient to realize substantial savings in transmission cost. We find that carefully designed proxy-assisted reactive transmission schemes can produce significant cost savings even in a predominantly unicast environment such as the Internet.     

Extension of practical channel transition broadcasting for near video-on-demand applications

Periodic broadcasting is a cost-effective solution for the large-scale distribution of popular videos. This strategy guarantees constant worst service latency to all clients, regardless of the number of video requests. The practical channel transition broadcasting (PCTB) scheme is an essential periodic broadcasting method that can dynamically add or release broadcasting channels (i.e., channel transition) according to video popularity. However, PCTB experiences bandwidth waste when performing channel transition. This study further finds that PCTB yields transition playback latency during channel addition. Therefore, an enhanced version referred to as PCTB+ is proposed to cause less bandwidth waste and lower transition playback latency. The applicability of this new scheme is verified, and an analytical evaluation is provided to demonstrate its performance advantage. The new scheme reduces bandwidth waste by 50 % to 100 % compared to the original PCTB scheme. Moreover, PCTB+ yields 50 % smaller transition playback latency than PCTB. The proposed scheme outperforms the seamless fast broadcasting (SFB) scheme for bandwidth waste under most conditions. No extra startup latency and client buffer demand are required when using PCTB+.     

端到端MPEG-4 FGS视频TCP友好的平滑传输

着重研究了Internet上MPEG-4 FGS(fine grained scalable)视频流的自适应平滑传输,其主要目的在于,在网络带宽变化的情况下,提供稳定的视频回放质量.提出了一种新的基于TFRC(TCP-friendly rate control)的MPEG-4 FGS端到端视频流传输系统框架,在此框架的基础上,首先假设完整的可用带宽变化已知,并且提出了一种离线的自适应平滑算法.此后,给出一种基于改进的ARAR(autoregressive autoregressive)预测技术的在线自适应平滑算法.最后,以NS-2为实验平台进行了模拟实验.模拟实验表明,提出的离线和在线自适应平滑算法可以充分利用可用网络带宽,并且能够在可用网络带宽持续波动的情况下保证接收方的回放尽可能地平稳,从而达到获得最佳视觉效果的目的.     

Content-Aware Distortion-Fair Video Streaming in Congested Networks

Internet is experiencing a substantial growth of video traffic. Given the limited network bandwidth resources, how to provide Internet users with good video playback quality-of-service (QoS) is a key problem. For video clips competing bandwidth, we propose an approach of Content-Aware distortion-Fair (CAF) video delivery scheme, which is aware of the characteristics of video frames and ensures max-min distortion-fair sharing among video flows. CAF leverages content-awareness to prioritize packet dropping during congestion. Different from bandwidth fair sharing, CAF targets end-to-end video playback quality fairness among users. The proposed CAF approach does not require rate-distortion modeling of the source, which is difficult to estimate. Instead, it exploits the temporal prediction structure of the video sequences along with a frame drop distortion metric to guide resource allocations and coordinations. Experimental results show that the proposed approach operates with limited overhead in computation and communication, and yields better QoS, especially when the network is congested.     

Strategies for adaptive smoothing and rebuffering via dynamic network calculus

This paper proposes an adaptive video smoothing and rebuffering algorithm for video transmission in best-effort, low-bandwidth networks. Our algorithm, which is derived from a “dynamic” extension of the network calculus, (1) detects whether playback disruptions are inevitable and, if so, schedules a rebuffering action with minimal rebuffering delay and (2) computes a conservative transmission schedule that ensures continuous playback while minimizing consumption of network available bandwidth. NS-2 simulation results show that, compared to an aggressive transmission strategy, our method can greatly reduce bandwidth consumption and, compared to a simple rebuffering strategy with the same bandwidth consumption, our method can effectively reduce total playback delay while also reducing the number of rebuffering events.     

A client-assisted interval caching strategy for video-on-demand systems

In a Video-on-Demand (VoD) system, in order to guarantee smooth playback of a video stream, sufficient resources (such as disk I/O (Input/Output) bandwidth, network bandwidth) have to be reserved in advance. Thus, given limited resources, the number of simultaneous streams can be supported by a video server is restricted. Due to the mechanical nature, the I/O subsystem is generally the performance bottleneck of a VoD system, and there have been a number of caching algorithms to overcome the disk bandwidth limitation. In this paper, we propose a novel caching strategy, referred to as client-assisted interval caching (CIC) scheme, to balance the requirements of I/O bandwidth and cache capacity in a cost-effective way. The CIC scheme tends to use the cache memory available in clients to serve the first few blocks of streams so as to dramatically reduce the demand on the I/O bandwidth of the server. Our objective is to maximize the number of requests that can be supported by the system and minimize the overall system cost. Simulations are carried out to study the performance of our proposed strategy under various conditions. The experimental results show the superior of CIC scheme to the tradition Interval Caching (IC) scheme, with respect to request accepted ratio and average servicing cost per stream.     

Smooth workload adaptive broadcast

The high-bandwidth requirements and long-lived characteristics of digital video make transmission bandwidth usage a key limiting factor in the widespread streaming of such content over the Internet. A challenging problem is to develop bandwidth-efficient techniques for delivering popular videos to a large, asynchronous client population with time-varying demand characteristics. In this paper, we propose smooth workload adaptive broadcast to address the above issues. A key component of our scheme is Flexible Periodic Broadcast (FPB). By introducing a feedback control loop into FPB, and enhancing FPB using techniques such as parsimonious transmission, smooth workload adaptive broadcast provides instantaneous or near-instantaneous playback services and can smoothly adapt to workload changes. Furthermore, FPB, as proposed in this paper, is bandwidth efficient and exhibits the periodic smooth channel transition property.     

Optimized scalable cache management for video streaming system

An important research issue in video streaming is how to efficiently utilize the network resources to provide clients instant access to multiple video objects. Caching strategy and transmission scheme are the two essential points inside the video streaming framework. Recent research efforts on them are not sufficient due to their inflexible support for scalable encoded video streams and heterogeneous requests from clients. In this paper, we propose an optimized caching strategy (OCS) and a scalable transmission scheme (STS) for scalable coded video streaming. By exploring the characteristics of video streaming workload and system design objectives, OCS and STS work efficiently to minimize both network bandwidth cost and user access latency. Firstly, we analyze the caching problem for the proxy-assisted video streaming system and derive a maneuverable caching scenario. Secondly, we develop an efficient transmission scheme for scalable coded videos. Thirdly, we formulate a multi-objective optimization model with closed-form expressions to obtain the optimized caching strategy. Finally, with designed algorithms, an excellent compromise between two competing objectives (minimizing the bandwidth cost and the access latency) is achieved. We start our evaluation by studying the optimized caching strategy for a single video object. Then we apply the strategy to multiple video objects and illustrate the tradeoff between the optimization objectives. Our evaluation results show that compared with other caching strategies, the proposed optimized scalable caching strategy can achieve a significant reduction in bandwidth cost with even a small proxy cache size. Meanwhile, the best performance (in terms of bandwidth cost) is obtained together with the proposed scalable batch-patching transmission scheme.

Scalable playback rate control in P2P live streaming systems

Current commercial live video streaming systems are based either on a typical client–server (cloud) or on a peer-to-peer (P2P) architecture. The former architecture is preferred for stability and QoS, provided that the system is not stretched beyond its bandwidth capacity, while the latter is scalable with small bandwidth and management cost. In this paper, we propose a P2P live streaming architecture in which by adapting dynamically the playback rate we guarantee that peers receive the stream even in cases where the total upload bandwidth changes very abruptly. In order to achieve this we develop a scalable mechanism that by probing only a small subset of peers monitors dynamically the total available bandwidth resources and a playback rate control mechanism that dynamically adapts playback rate to the aforementioned resources. We model analytically the relationship between the playback rate and the available bandwidth resources by using difference equations and in this way we are able to apply a control theoretical approach. We also quantify monitoring inaccuracies and dynamic bandwidth changes and we calculate dynamically, as a function of these, the maximum playback rate for which the proposed system able to guarantee the uninterrupted and complete distribution of the stream. Finally, we evaluate the control strategy and the theoretical model in a packet level simulator of a complete P2P live streaming system that we designed in OPNET Modeler. Our evaluation results show the uninterrupted and complete stream delivery (every peer receives more than 99 % of video blocks in every scenario) even in very adverse bandwidth changes.     

请求下降邻域叠加选取分布式P2P 视频点播调度

为实现对等架构的低成本视频流传输和实时播放要求,提出基于请求下降叠加选 取的分布式P2P 视频点播调度算法。首先,基于叠加技术构建P2P 视频点播的技术指标,充分 考虑输入邻域节点、输出邻域节点和媒体服务器负载3 组优化指标,构建叠加架构和分布式算 法流程;其次,利用请求下降策略对发送节点和服务节点选取进行改进,解决可能出现的带宽 低利用率和无效的视频播放问题;最后,通过BitTorrent 视频点播系统对所提算法的有效性进 行了验证。     

IEEE 802.11e网络中传输可分级视频流的调度方案

在保证可分级视频流延时要求的情况下,为了有效提高其在无线网络中传输的带宽利用率,提出了一种新的调度方案。该方案利用可分级视频流的分解特性以及不同的流采用不同的调度周期来提高带宽利用率。数值结果表明该方案非常有效,特别是当物理层传输速率较大的时候,其有效性更加明显。     

IP网络环境下基于PI控制的实时视频流连续播放控制算法

为了克服IP网络环境下网络扰动对流媒体连续播放的影响,从接收端的角度来解决流媒体连续播放问题,提出一种基于PI控制的实时视频流连续播放控制算法.该方法在接收端使用根轨迹法设计PI控制器,通过控制播放速率,调节缓冲区的长度,实现了媒体的连续播放.为了真实地反映网络传输对接收端播放的影响,本文构建了一种基于TFRC协议的实时视频流传输控制框架.NS2仿真实验表明该方法与其他方法相比,播放质量明显提高,缓冲区出现欠载和溢出的机率明显降低,视频帧端到端平均时延明显缩小,实时性能明显增强.     

Efficient compression and network adaptive video coding for distributed video surveillance

The availability of cheap network based video cameras and the prevalence of wireless networks has lead to a major thrust towards deployment of large scale Distributed Video Surveillance (DVS) systems. This has opened up an important area of research to deal with the issues involved in DVS system for efficient collection and transmission of large scale video streams from the cameras at the guarded sites, to the end users in possibly constrained network conditions. In this paper, we propose a framework based on content-based video classification and scalable compression scheme to provide a robust bandwidth efficient video transmission for DVS. The scheme builds on a Discrete Wavelet Transform (DWT) based Color-Set Partitioning for Hierarchical Trees (CSPIHT) coding to obtain a scalable bitstream. Wavelet domain segmentation and compression assists in development of a DVS architecture. The architecture includes a novel module for dynamic allocation of Network bandwidth based on the current available resources and constraints. Different frame constituents are optimally coded based on their relative significance, perceptual quality, and available estimate of network bandwidth. Experimental result over different video sequences and simulations for Network conditions demonstrate the efficient performance of the approach.     

大数据量实时视频流传输拥塞控制研究

大数据量实时视频流传输系统有广泛的应用前景。大数据量、高带宽要求的视频流传输中存在许多问题。网络的负载均衡、视频的回放质量都将严重影响整个网络的安全以及传输系统的应用。通过对丢包率进行卡尔曼过滤(Kalman Filter)分析预测网络负载状况、结合接收缓冲区大小设置来平滑发送速率,在分析TCP友好拥塞控制的基础上,提出了一种基于RTCP反馈的TCP友好(TCP-Friendly)对该机制的TCP友好性、视频的回放质量进行了实验和结果分析。     

Adaptive topology formation for peer-to-peer video streaming

In this paper we propose an adaptive P2P video streaming framework to address the challenges due to bandwidth heterogeneity and peer churn on the Internet. This adaptive streaming framework consists of two major components, source rate adaptation and adaptive overlay topology formation, to maximize the video quality and fully utilize the overall peer upload capacity. In the source rate adaptation, the video server adapts the video source rate automatically based on the local measurement of peers’ download rates, so that the P2P network is not overloaded beyond its bandwidth capacity and peers are able to achieve smooth video playback. To combat bandwidth heterogeneity, we propose to construct a desirable link-level homogeneous overlay topology using a Markov chain Monte Carlo method, so that peers achieve an equal per-connection upload/download bandwidth. In this link-level homogeneous network, video flows do not encounter any bottlenecks along the delivery paths, and peers achieve high download rates to ensure smooth video playback. We also design a fully distributed algorithm to implement the dual mechanisms of the adaptive topology formation and the source rate maximization. To evaluate the performance of our streaming framework, we conduct both mathematical analysis and extensive simulations. The simulation results confirm our analysis and show that the proposed distributed algorithm is able to maximize the video playback quality with fast convergence.