Adaptive low-latency peer-to-peer streaming and its application

Peer-to-peer (P2P) streaming is emerging as a viable communications paradigm. Recent research has focused on building efficient and optimal overlay multicast trees at the application level. A few commercial products are being implemented to provide voice services through P2P streaming platforms. However, even though many P2P protocols from the research community claim to be able to support large scale low-latency streaming, none of them have been adopted by a commercial voice system so far. This gap between advanced research prototypes and commercial implementations shows that there is a lack of a practical and scalable P2P system design that can provide low-latency service in a real implementation. After analyzing existing P2P system designs, we found two important issues that could lead to improvements. First, many existing designs that aim to build a low-latency streaming platform often make the unreasonable assumption that the processing time involved at each node is zero. However in a real implementation, these delays can add up to a significant amount of time after just a few overlay hops and make interactive applications difficult. Second, scant attention has been paid to the fact that even in a conversation involving a large number of users, only a few of the users are actually actively speaking at a given time. We term these users, who have more critical demands for low-latency, active users. In this paper, we detail the design of a novel peer-to-peer streaming architecture called ACTIVE. We then present a complete commercial scale voice chat system called AudioPeer that is powered by the ACTIVE protocol. The ACTIVE system significantly reduces the end-to-end delay experienced among active users while at the same time being capable of providing streaming services to very large multicast groups. ACTIVE uses realistic processing assumptions at each node and dynamically optimizes the streaming structure while the group of active users changes over time. Consequently, it provides virtually all users with the low-latency service that before was only possible with a centralized approach. We present results from both simulations and our real implementation, which clearly show that our ACTIVE system is a feasible approach to scalable, low-latency P2P streaming.     

Video streaming over the internet with optimal bandwidth resource allocation

In this paper, an adaptive framework for video streaming over the Internet is presented. The framework is a joint design of packet scheduling and rate control with optimal bandwidth resource allocation. The transmission rate is dynamically adjusted to obtain maximal utilization of the client buffer and minimal allocation of the bandwidth. Under the constraint of the transmission rate, a prioritized packet scheduling is designed to provide a better visual quality of video frames. The packet scheduling is a refined bandwidth allocation which takes into account of varying importance of the different packets in a compressed video stream. Moreover, the proposed approach is scalable with increasing multimedia flows in the distributed Internet environment. Comparisons are made with the most current streaming approaches to evaluate the performance of the framework using the H.264 video codec. The extensive simulation results show that the average Peak Signal to Noise Ratio (PSNR) increases in our proposed approach. It provides a better quality of the decoded frames, and the quality of the decoded frames changes more smoothly. The achieved video quality among different users also has a lower fluctuation, which indicates a fair sharing of network resources.

视频实时传输中的速率控制研究

视频在互联网上的实时传输常因其要求高带宽、低延迟而造成网络拥塞。传统TCP基于窗口的拥塞控制已经不适用于实时传输中的拥塞控制,该文讨论了基于速率的网络拥塞控制方法,它采用自适应码率和分层的视频编码技术,详细说明了基于源端和收端的各种速率控制方法。     

Storage technique for real-time streaming of layered video

Scalable streaming technology has been proposed to effectively support heterogeneous devices with dynamically varying bandwidth. From the file system’s point of view, scalable streaming introduces another dimension of complexity in disk scheduling. Most of the existing efforts on multimedia file systems are dedicated to I/O scheduling algorithm and data placement scheme that efficiently guarantee I/O bandwidth. The important underlying assumption in these efforts is that most of the multimedia file accesses are simple playback operations and therefore are sequential. However, this workload characteristic is not valid in scalable streaming environment. In a scalable streaming environment, i.e., when only a subset of imagery is retrieved, the playback does not necessarily coincide with the sequential access on the file. The current file structure and the file system organization leaves much to be desired for supporting scalable streaming service. In this work, we propose a file system scheme, Harmonic Placement to efficiently support scalable streaming. The basic idea of Harmonic placement is to cluster the frequently accessed layers together to avoid unnecessary disk seeks. The data blocks are partitioned into two sets with respect to the layers: lower layers and upper layers. In Harmonic placement, the data blocks in the lower layers are placed with respect to their frame sequence and the data blocks in the upper layers are clustered according to the layers they belong to. We develop elaborate performance models for three different file system schemes: Progressive placement, Interleaved Placement and Harmonic Placement. We investigate the performance of the file server with different file system schemes. It was found that file system performance is very sensitive to the file organization scheme. When most of the service requests are for low-quality video (e.g., 128 Kbits/s ISDN), Progressive placement scheme supports twice as many sessions as the Interleaved placement scheme. When most of the service requests are for high-quality video (e.g., 1.5 Mbits/s MPEG-2 DVD quality), Interleaved placement can support twice as many requests as Progressive placement. In both cases, Harmonic placement scheme yields the most promising performance. Primitive version of this work has appeared on Proceedings of NOSSDAV ’06, Providence, Rhode Island, USA. This work is in part funded by KOSEF throught National Research Lab (ROA-2007-000-200114-0) and by HY-SDR center at Hanyang University.     

CollectCast: A peer-to-peer service for media streaming

We present CollectCast, a peer-to-peer (P2P) service for media streaming where a receiver peer is served by multiple sender peers. CollectCast operates at the application level but infers underlying network properties to correlate end-to-end connections between peers. The salient features of CollectCast include: (1) a novel multisender selection method that exploits the performance correlation and dependency among connections between different candidate senders and the receiver, (2) a customization of network tomography techniques and demonstration of improved practicality and efficiency, and (3) an aggregation-based P2P streaming mechanism that sustains receiver-side quality in the presence of sender/network dynamics and degradation. We have performed both real-world (on PlanetLab) and simulation evaluation of CollectCast. Our simulation results show that for a receiver, CollectCast makes better selection of multiple senders than other methods that do not infer underlying network properties. Our PlanetLab experiments are performed using a P2P media streaming application (called PROMISE) which we developed on top of CollectCast. Both packet-level and frame-level performance of MPEG-4 video streaming demonstrates the practicality and effectiveness of CollectCast.     

Modeling and analysis for streaming service systems

The proliferation of streaming service system in various application areas gains increasing importance and also poses more challenges in the research of streaming service system. In this paper, we propose a novel dynamic model composed of a set of differential equations to describe the evolution of streaming service systems. And in the model, we focus on how the policies for admission control and peer selection influence on the system. We first introduce a flexible abstraction of streaming service systems. The abstraction is generally enough to capture the essences of streaming service systems with different structures, physical characteristics, software protocols and client behaviors. Then, by analyzing the state which is defined as the number of requests, a novel dynamic model is developed in microscopic scale to characterize the behaviors of streaming service systems. The model proposed in this paper demonstrates the interactions between clients and servers and also between different servers. The interactions are primarily influenced by the admission control policy and peer selection policy. Finally, some experiments are designed to verify the validation and reasonability of the model.     

基于H.264可伸缩视频流的自适应媒体播放算法

为了应对H.264可伸缩视频编码（SVC）应用中网络特性的波动,提出了一种预测播放中断与缓冲区溢出风险进行及早调节的自适应媒体播放(AMP)算法。该算法估算网络流量与视频图像组（GOP）结构中各帧长度用于风险预测,通过K步调节过程实现良好的调节平滑性与速度,并利用SVC的可伸缩性尽量减少溢出带来的质量损失。仿真结果表明,该算法在抑制播放中断、处理缓冲区溢出与抖动性能等方面,优于现行的平滑AMP与常规AMP算法。     

Transmission of layered video streaming via multi-path on ad hoc networks

Mobile ad hoc networks without centralized infrastructure change their topology rapidly because of node mobility, making multimedia applications difficult to run across wireless networks. Moreover, video transmission over ad hoc networks causes frequent transmission loss of video packets owing to end-to-end transmission with a number of wireless links, and requires essential bandwidth and restricted delay to provide quality-guaranteed display. This paper presents an architecture supporting transmission of multiple video streams in ad hoc networks by establishing multiple routing paths to provide extra video coding and transport schemes. This study also proposes an on-demand multicast routing protocol to transport layered video streams. The multicast routing protocol transmits layered video streaming based on a weight criterion, which is derived according to the number of receivers, delay and expiration time of a route. A simulation is performed herein to indicate the viability and performance of the proposed approach. The simulation results demonstrate that the proposed transport scheme is more effective than other video transport schemes with single or multiple paths.

Analysis of a CDN–P2P hybrid architecture for cost-effective streaming media distribution

To distribute video and audio data in real-time streaming mode, two different technologies – Content Distribution Network (CDN) and Peer-to-Peer (P2P) – have been proposed. However, both technologies have their own limitations: CDN servers are expensive to deploy and maintain, and consequently incur a cost for media providers and/or clients for server capacity reservation. On the other hand, a P2P-based architecture requires sufficient number of seed supplying peers to jumpstart the distribution process. Compared with a CDN server, a peer usually offers much lower out-bound streaming rate and hence multiple peers must jointly stream a media data to a requesting peer. Furthermore, it is not clear how to determine how much a peer should contribute back to the system after receiving the media data, in order to sustain the overall media distribution capacity.In this paper, we propose and analyze a novel hybrid architecture that integrates both CDN- and P2P-based streaming media distribution. The architecture is highly cost-effective: it significantly lowers the cost of CDN capacity reservation, without compromising the media quality delivered. In particular, we propose and compare different limited contribution policies for peers that request a media data, so that the streaming capacity of each peer can be exploited on a fair and limited basis. We present: (1) in-depth analysis of the proposed architecture under different contribution policies, and (2) extensive simulation results which validate the analysis. Our analytical and simulation results form a rigorous basis for the planning and dimensioning of the hybrid architecture.     

Towards efficient video chunk dissemination in peer-to-peer live streaming

There are substantial differences in chunk dissemination manner between P2P live streaming and BitTorrent, and inappropriate algorithms will result in inefficiency of live streaming systems. In this paper, we study the chunk dissemination of P2P live streaming, and introduce a discrete and slotted mathematical model to analyze chunk selection algorithms, including rarest first algorithm and greedy algorithm. Moreover, we present a performance metric to evaluate chunk selection algorithms, as well as the optimization function for the exploration of chunk dissemination strategies. We point out the causes of poor performance of these algorithms, and propose a service request randomization mechanism to promote the use of peer resources, which can prevent chunk requests from rendezvous on a few of peers. Simultaneously, we employ weight assignment strategies to avoid excessive requests for rare chunks. Besides, we present an enhanced model, which adds node degree constraint, to improve our model. We revisit the chunk selection algorithms based on the enhanced model. The results of simulation experiments validate our theoretical analysis and indicate that the weighted randomization mechanism is resilient to flash crowd and peer churn, and can improve the performance of P2P live streaming.     

Quality adaptive end-to-end packet scheduling to avoid playout interruptions in Internet video streaming systems

In Internet multimedia streaming, the quality of the delivered media can be adapted to the Quality of Service provided by the underlying network, thanks to encoding algorithms. These allow a fine grained enhancement of a low quality base layer at streaming time. The main objective that should be satisfied in such systems is to avoid the starvation of the decoding process and consequent playout interruptions. In this work, we tackle the problem using a control theoretic approach. In particular, we design and implement the novel end-to-end Quality Adaptive Scheduler for properly distributing the network available bandwidth among base and enhancement layers. The developed solution can be adopted in many contexts given that it has been designed without assumptions on the delivered media nor on the protocol stack. Anyway, to test its effectiveness, we have casted it in a H.264/AVC SVC based video streaming architecture for unicast Internet applications. The performance of the scheduler has been experimentally evaluated in both a controlled testbed and several “wild” Internet scenarios, including also UMTS and satellite radio links. Results have clearly demonstrated that our Quality Adaptive Scheduler is able to significantly improve the performance of the video streaming system in all operative conditions.     

视频流自适应传输技术研究

对当前视频流技术所采取的各种压缩算法及标准、传输协议、拥塞控制等技术进行了总结与分析,在此基础上对IP网络上的视频流自适应传输技术进行了研究,建立了实现该技术的框架。此技术框架综合了实时的视频自适应编码技术和有效的带宽自适应传输技术。实验结果表明,在对视频流的实时性要求高的应用上具有较突出的优势。     

多媒体直播课堂软件系统的设计

针对目前多媒体教室的资源不能被远程教育的学生有效利用的现象,结合音频、视频和屏幕图像压缩算法的压缩比率不断提高的特点,提出了一种多媒体直播课堂软件系统,给出了其系统框架,并详细介绍了该系统的Web服务器、编码服务器、直播服务器、流媒体代理服务器和客户端的设计.该系统与类似系统相比,不受电子讲稿种类多样性的限制,可适应更多的多媒体压缩算法,在传输效率上也有一定的优势.     

基于电量状态的移动流媒体码率自适应策略

为提升移动流媒体的用户体验质量(quality of experience,QoE)和设备续航时长,提出一种基于移动设备电量状态的Qo E模型,模型的参数包括初始延迟、重新缓冲、平均视频质量、码率切换平滑度以及设备电量状态.在模型的基础上,给出一种基于网络吞吐量,同时又考虑设备电量状态的码率自适应策略.策略能避免客户端...     

RTP自适应传输控制算法的研究

RTP自适应传输控制算法是在基于实时传输协议（RTP）的流媒体服务中进行端到端流量控制的算法,对于保证流媒体服务质量有重要作用。本文详细介绍了流媒体传输对RTP自适应传输控制算法的要求,对现有算法的各个组成棋块进行了深入分析;总结了目前RTP自适应传输控制算法的特点,指出了该算法今后研究和设计的趋势。     

自适应流媒体传输方案研究及其应用

提出了一种自适应流媒体传输方案，根据网络状况调整视频数据的发送速率和视频流的码率，以保证视频数据顺利及时的传输到客户端，使客户端能够顺利进行高质量的媒体播放。该方案涵盖了码率整形、拥塞控制和视频质量自适应等功能模块及其相互关系，各功能模块可以依据应用需求选择算法加以具体实现，从而提高了方案的可扩展性和灵活性。所以该方案不依赖于具体的视频编码标准和网络协议，适用范围较广。文中还基于实际流媒体服务器给出了该方案的一个实际应用，点播测试实验汪明该方案是有效的。     

视频通信的网络自适应传输控制技术

针对视频传输中的拥塞控制问题,对网络自适应传输控制技术进行了研究,该技术综合了UDP与TCP的传输特性,能够对网络拥塞进行自适应控制。提出了该技术的技术框架和实现方案,并将其应用在一个端到端的视频传输系统中。实验结果表明,网络自适应传输控制技术可以为视频通信提供良好的传输质量保障。     

运动感知基于缓存的自适应视频流传输

目的 基于缓存的自适应视频流传输策略无需估测实时带宽,直接通过缓存变化量与码率的映射函数选取符合当前网络状况的最佳质量码流传输。传统基于缓存的自适应视频传输不考虑内容特征,在码率选择上为不同运动级别视频内容均使用相同的码率映射函数,在不稳定的无线网络环境中高运动强度内容的码率急剧降低会严重伤害用户体验质量（QoE）,提出运动感知基于缓存的自适应视频流传输（MA-BBA）算法。方法 MA-BBA算法根据片段运动级别确定码率映射函数,对运动强度高的内容快速切换到较高码率,而对于运动强度较低的内容则使用较为保守的码率,从而使得缓存资源能够位于安全边界之上且较多分配给高级别运动内容,提高不同运动强度内容的平均质量,使整体QoE得到优化。结果 在公开的无线网络带宽数据集上实现本文MA-BBA算法,基于吞吐量的自适应传输算法（TBA）和基于缓存的自适应传输算法（BBA）。MA-BBA在高运动强度内容的平均质量上比TBA和BBA分别提高1.7%和1.2%,且质量波动区间更小。MA-BBA在平均缓存利用率上达到72%,大大高于TBA的45.9%和BBA的45.4%。结论 MA-BBA算法与现有的码率自适应算法TBA和BBA相比,大大提高了缓存资源利用率,提高了对资源要求最苛刻的高级别运动内容的传输质量,减小码率切换幅度频率,优化了视频服务的整体QoE。