Adaptive delivery of immersive 3D multi-view video over the Internet

The increase in Internet bandwidth and the developments in 3D video technology have paved the way for the delivery of 3D Multi-View Video (MVV) over the Internet. However, large amounts of data and dynamic network conditions result in frequent network congestion, which may prevent video packets from being delivered on time. As a consequence, the 3D video experience may well be degraded unless content-aware precautionary mechanisms and adaptation methods are deployed. In this work, a novel adaptive MVV streaming method is introduced which addresses the future generation 3D immersive MVV experiences with multi-view displays. When the user experiences network congestion, making it necessary to perform adaptation, the rate-distortion optimum set of views that are pre-determined by the server, are truncated from the delivered MVV streams. In order to maintain high Quality of Experience (QoE) service during the frequent network congestion, the proposed method involves the calculation of low-overhead additional metadata that is delivered to the client. The proposed adaptive 3D MVV streaming solution is tested using the MPEG Dynamic Adaptive Streaming over HTTP (MPEG-DASH) standard. Both extensive objective and subjective evaluations are presented, showing that the proposed method provides significant quality enhancement under the adverse network conditions.     

Rate-sensitive leverage of QoS and QoP for ubiquitous video streaming via buffer-aware feedback control

Providing real-time Internet video streaming anytime, anywhere and using any devices from different access networks preserves more challenges to equilibrate the quality of service (QoS) and security protection (QoP). Because encryption/decryption for video packets are time-consuming processes to protect real-time video streaming services from eavesdropping, our observation is that the playback buffer occupancy (PBO) can simply indicate time availability to adjust security level to affect the packet sending rate. In this paper, we present an end-to-end buffer-aware feedback control from client PBO for effectively securing media streaming for heterogeneous clients over ubiquitous Internet. That is, security-level adjustments can be applied further to keep PBO running away from overflow and underflow to pursue an effective leverage between QoS and QoP. To further boost the protection, we also apply the Diffie-Hellman key negotiation method to provide the dynamic key changes. Moreover, since the running PBO will vary on the dynamics of Internet from access time, client devices and access networks, the different applied security levels and key changes during the video streaming session will make eavesdropper more difficult to recover all the encrypted videos delivered in public networks. We demonstrate the leverage performance in preserving both QoS and QoP for ubiquitous video streaming in our proposed schemes by comprehensive experiments on a true VoD system. The experimental results show our secure VoD scheme can achieve cost-effective leverage of QoS and QoP from different inserted network dynamics, even if client buffer size is limited to 256 KB only.     

An efficient scheduling algorithm for scalable video streaming over P2P networks

During recent years, the Internet has witnessed rapid advancement in peer-to-peer (P2P) media streaming. In these applications, an important issue has been the block scheduling problem, which deals with how each node requests the media data blocks from its neighbors. In most streaming systems, peers are likely to have heterogeneous upload/download bandwidths, leading to the fact that different peers probably perceive different streaming quality. Layered (or scalable) streaming in P2P networks has recently been proposed to address the heterogeneity of the network environment. In this paper, we propose a novel block scheduling scheme that is aimed to address the P2P layered video streaming. We define a soft priority function for each block to be requested by a node in accordance with the block’s significance for video playback. The priority function is unique in that it strikes good balance between different factors, which makes the priority of a block well represent the relative importance of the block over a wide variation of block size between different layers. The block scheduling problem is then transformed to an optimization problem that maximizes the priority sum of the delivered video blocks. We develop both centralized and distributed scheduling algorithms for the problem. Simulation of two popular scalability types has been conducted to evaluate the performance of the algorithms. The simulation results show that the proposed algorithm is effective in terms of bandwidth utilization and video quality.     

基于P2P视频点播技术的流媒体平台设计与开发

随着流媒体应用在Internet上的流行,传统C/S模式的流媒体服务系统已经不能满足流媒体对服务器性能和高带宽的要求,严重阻碍了流媒体业务质量的提高和容量的扩大。本文介绍一种基于P2P网络的流媒体播放技术,它将P2P网络技术和流媒体技术结合起来,充分利用客户计算机的资源,减轻流媒体服务器和网络负载,突破了传统的流媒体播放系统带宽瓶颈,能够保持播放节目流完整而流畅。本文还采用MVC模式和Java语言以面向对象方法设计和开发P2P流媒体网站,利用P2P流媒体技术,实现校园流媒体的视频点播。     

一种无线实时流媒体增强型自适应FEC控制机制

无线网络动态的信道特性和带宽有限等特点,使得在无线环境下为流媒体应用提供QoS保证面临更大的挑战。提出一种用于无线实时流媒体传输的增强型自适应前向纠错控制策略,以提高接收方的播放质量。该策略采用跨层设计的方法,根据当前的网络状态,自适应地调整MPEG视频帧的发送速率,在视频源数据和冗余数据之间动态分配网络带宽。仿真结果表明,该策略能使接收方获得最大的可播放帧率,有效提高流媒体传输的可靠性和实时性。     

Empirical evaluation of the congestion responsiveness of RealPlayer video streams

Increasingly popular commercial streaming media applications over the Internet often use UDP as the underlying transmission protocol for performance reasons. Hand-in-hand with the increase in streaming media comes the impending threat of unresponsive UDP traffic, often cited as the major threat to the stability of the Internet. Unfortunately, there are few empirical studies that analyze the responsiveness, or lack of it, of commercial streaming media applications. In this work, we evaluate the responsiveness of RealNetworks’ RealVideo over UDP by measuring the performance of numerous streaming video clips selected from a variety of RealServers on the Internet, analyze the TCP-Friendliness of the UDP streams and correlate the results with network and application layer statistics. We find that most RealVideo UDP streams respond to Internet congestion by reducing the application layer encoding rate, and streams with a minimum encoding rate less than the fair share of the capacity often achieve a TCP-Friendly rate. In addition, our results suggest that a reason streaming applications choose not to use TCP is that the TCP API hides network information, such as loss rate and round-trip time, making it difficult to estimate the available capacity for effective media scaling.     

Packet loss in peer-to-peer video streaming over the Internet

Peer-to-peer streaming has recently gained attention as an effective solution to support large scale media streaming applications over the Internet. One of the main challenges of peer-to-peer video streaming is the cumulative impact of the Internet packet loss due to the decoding dependency of the compressed video frames. In this paper we study the impact of the Internet packet loss on the performance of peer-to-peer video streaming systems, and analyze the efficiency of various packet loss recovery policies in such systems. Our analytical and simulation results show how the Internet packet loss can affect the performance of peer- to-peer video streaming systems and how different packet loss recovery policies can be effective for such systems. Our analysis results give us some insights that can be used in designing efficient peer-to-peer video streaming systems.     

基于视频发送端速率控制的QoS技术研究

基于尽力而为的网络模式不能提供QoS保证,网络拥塞和分组丢失不可避免。在端到端视频单播结构下,论文提出了一个发送端速率控制框架SRCF,在此框架下首先利用RTCP报文中的字段提出了一种网络参数测量方法,然后设计了一个自适应速率算法SRCA,SRCA利用已得到的网络传输延迟和分组丢失率参数作为初始参数,来调整编码速率,达到充分利用带宽的目的,避免了视频质量由于调整参数带来的剧烈抖动。仿真结果表明,该算法在网络出现一定拥塞的条件下,能跟踪带宽的变化,网络和媒体QoS能保证视频质量较好。     

一种基于视频分类的码率自适应算法

流媒体的码率自适应算法依据网络状态动态调节视频块的码率,提升用户体验质量,但忽略了视频类型的差异对用户体验质量的影响,导致算法性能下降。提出区分视频类型特征的码率选择算法C-ABR。设计相应的用户体验质量效用函数,使用强化学习算法训练模型A3C,提升用户体验质量。实验结果说明,相对于典型的码率自适应算法Pensieve和MPC,C-ABR算法用户体验质量分别提升22.7%和50.4%。     

IEEE 802.21-based seamless multicast streaming with dynamic playback control

With the explosion of video streaming available on the Internet, online multimedia applications become more popular in our days and the video quality of the Internet multimedia applications is directly affected by the network transmission state, which will be worse while switching the ongoing network connection from one wireless interface to another heterogeneous wireless technology, such as IEEE 802 families, UMTS (universal mobile telecommunications system) network and 3GPP LTE (3rd generation partnership project-long term evolution). In order to perform seamless handover between heterogeneous wireless networks, IEEE group proposed the “IEEE 802.21 standard” and defined a middleware function called “media independent handover function (MIHF)” to smooth the handover. In this paper, a dynamic playback control for multicasting streaming based on IEEE 802.21 is proposed to reduce the influence of handover between heterogeneous networks. In addition, we evaluate three different rate modes for seamless multicasting streams. The simulation results show that different playback frame rate modes, including the usual, incremental and linear modes, can achieve different video quality and can extend the playing time for handover video playback.     

基于流媒体相关的视频安全组播协议(MSMP)研究

随着无线网络的快速发展和Internet中流媒体视频的巨大成功,无线网络中的视频服务有望在不久的将来得到大规模部署,无线网络上的实时流媒体传输技术已成为研究热点,而其中视频安全组播协议是一个关键问题。但是,由于无线网络中有限的带宽和有限的存储空间,外部的攻击与自适应机制带来的安全性问题在无线流媒体视频中是不可避免的。一个精心设计的密钥管理算法不仅可以明显地提高流媒体视频的性能,还能够保证可靠的数据嵌入以及实时视频应用提供安全支持。如何设计一个高效的密钥管理算法,是当前流媒体视频应用中一个备受关注的问题。针对无线视频应用,针对一个处于开放和不安全的网络环境中的自适应视频应用的密钥管理算法进行了研究,并进行了算法评价。     

Modeling and evaluating IPTV applications in WiMAX networks

Internet Protocol-based Television (IPTV) is a digital television service which delivers television content via an IP network. The rapid growth of wireless network technology in recent years has changed, the way people access the Internet. Adding mobility to IPTV can create a truly compelling ubiquitous service which spans different network domains and varied IP-enabled terminals and devices, such as set-top boxes, PCs and cell phones. However, extending IPTV service to wireless networks requires overcoming bandwidth bottlenecks and high packet loss rates. Following the IEEE 802.16 standard, worldwide interoperability for microwave access (WiMAX) features high data rates and large service coverage, offering a wireless broadband solution for IPTV services. While previous research has focused on creating a broadband IPTV service few studies have practically evaluated IPTV applications in a wireless broadband network environment. In this paper, we model and evaluate a common constant bit rate (CBR)¹ based IPTV application and an IPTV live streaming (PPStreaming)² application while retrieving IPTV content via a WiMAX network. We also use the NS2 simulation tool to evaluate the performance of these two IPTV applications. The evaluation metrics include latency, packet loss, data rate and throughput statistics when the two IPTV applications are run in the WiMAX network. ¹The simplest IPTV solution is to convey video content by CBR. IPTV operators and content delivery networks relay CBR streaming content to control the demand for network capacity. Broadcasters prefer CBR video as it conserves bandwidth resources, but CBR delivery can degrade video quality result in higher overall demand on network capacity. ²PPStreaming (also referred to as P2P streaming Internet TV) is a network for live media streaming. In principle it’s similar to BitTorrent (BT) in that it provides stable and smooth broadcast of TV programs to broadband users. Unlike traditional streaming media, PPStreaming adopts P2P-streaming technology and supports full-scale visits with tens of thousands of simultaneous users. Its client software can be used in the browser or as a standalone executable.     

Optimized streaming media proxy and its applications

Multimedia streaming is one of the most popular services on the current Internet. However, the major problem hinders streaming media applications is the network bandwidth. In this paper, we put forward a optimized streaming proxy system and think of utilizing it in peer-to-peer (P2P) applications. The main contribution of our proxy system is RTP segments splicing, prefix caching size determination and prefetching techniques, which are detailed discussed in this paper. By validating our implementation, the experimental results show that the streaming proxy can effectively contribute to reduce the server and backbone network load, thus achieve improved media quality and scalability. In addition, P2P network is a fascinate way for Internet resource sharing, many of researchers are devoting to research on P2P-based client communications. In our project, we make use of our proxy prototype into the streaming sharing over P2P network, each peer node just like a lightweight proxy between the server and the target peers. The real-time video sharing (RVS) system efficiently utilizes network bandwidth between peer clients through combining with our proxy as expected.     

Smooth Control of Adaptive Media Playout for Video Streaming

Client-side data buffering is a common technique to deal with media playout interruptions of streaming video caused by network jitters and packet losses of best-effort networks. However, stronger playout interruption protection inevitably amounts to larger data buffering and results in more memory requirements and longer playout delay. Adaptive media playout (AMP), also a client-side technique, can reduce the buffer requirement and avoid buffer outage but at the expense of visual quality degradation because of the fluctuation of playout speed. In this paper, we propose a novel AMP scheme to keep the video playout as smooth as possible while adapting to the channel condition. The triggering of the playout control is based on buffer variation rather than buffer fullness. Experimental results show that our AMP scheme surpasses conventional schemes in unfriendly network conditions. Unlike previous schemes that are tuned for a specific range of packet loss and network instability, the proposed AMP scheme maintains consistent performance across a wide range of network conditions.     

An incentive scheduling mechanism for peer-to-peer video streaming

P2P video streaming networks are found as a scalable solution and an alternative for traditional client–server based video streaming over the Internet. One of the significant issues affecting the success of any P2P streaming network is cooperation between peers. Practical observations have proved the prevalence of free riders in P2P networks that degrade their performance. To solve this problem, using incentive mechanisms, which encourage peers to contribute more in the network, is necessary. In this paper, we designed and proposed a distributed and scalable incentive mechanism for mesh based P2P video streaming networks. In the proposed approach the contribution of the peers is measured and maintained in a distributed fashion. Furthermore, we proposed an incentive sending side scheduler in which peers are served based on their contribution in the network. Our simulation evaluations show the efficiency of the proposed approach in improving the overall perceived video quality by the non-free rider nodes and consequently in the whole network.     

CStream: neighborhood bandwidth aggregation for better video streaming

Despite the popularity of watching videos online, challenges still remain in video streaming in many scenarios. Limited home broadband and mobile phone 3G bandwidths mean many users stream videos at compromised quality. To provide additional bandwidth for streaming, we propose CStream, a system that aggregates bandwidth from multiple cooperating users in a neighborhood environment for better video streaming. CStream exploits the fact that wireless devices have multiple network interfaces and connects cooperating users with a wireless ad-hoc network to aggregate their unused downlink Internet bandwidth. CStream dynamically generates a streaming plan to stream a single video using multiple connections, continuously adapting to changes in the neighborhood and variations in the available bandwidth. CStream is developed and evaluated on a test bed of computers, allowing for a detailed, controlled evaluation of performance. Analysis of the results shows a linear increase in throughput over single-connection streaming and improved video quality as the number of cooperating users in a neighborhood increase.     

A P2P streaming architecture supporting scalable media

Peer-to-peer (P2P) streaming solutions are changing the way real-time multimedia transmission is distributed over the Internet. The advances in video coding, like Scalable Video Coding, also turns possible high-quality/definition video distribution and consumption. The recent push in using the standard HTTP protocol for streaming videos in the World Wide Web, is also making converged entertainment services come closer to global deployment across TV, Tablet and mobile devices. The combination of Scalable Video, P2P networks and Web technologies for transmitting high-quality live and time-shifted media contents, is a potential area of innovation and a very actual research topic. This paper describes the architecture of a quality-centric P2P distribution network supporting adaptive and scalable streamable media, that decouples the transport mechanisms from the media content type and structure (video, audio, timed-data, timed-text), irrespective of their encoding schemes. The set of P2P streaming protocols designed for the network enables streaming of live and on-demand media, with very low signaling cost. Prototypes of the P2P network components were implemented and integrated in the streaming platform of EU FP7 SARACEN Project. A suite of tests for evaluation of the performance of the solution demonstrates that it keeps a fairly stable quality level with reduced amplitude and frequency of variations, raising the overall quality perceived by the end-user.     

Caching strategies in transcoding-enabled proxy systems for streaming media distribution networks

With the wide availability of high-speed network access, we are experiencing high quality streaming media delivery over the Internet. The emergence of ubiquitous computing enables mobile users to access the Internet with their laptops, PDAs, or even cell phones. When nomadic users connect to the network via wireless links or phone lines, high quality video transfer can be problematic due to long delay or size mismatch between the application display and the screen. Our proposed solution to this problem is to enable network proxies with the transcoding capability, and hence provide different, appropriate video quality to different network environment. The proxies in our transcoding-enabled caching (TeC) system perform transcoding as well as caching for efficient rich media delivery to heterogeneous network users. This design choice allows us to perform content adaptation at the network edges. We propose three different TeC caching strategies. We describe each algorithm and discuss its merits and shortcomings. We also study how the user access pattern affects the performance of TeC caching algorithms and compare them with other approaches. We evaluate TeC performance by conducting two types of simulation. Our first experiment uses synthesized traces while the other uses real traces derived from an enterprise media server logs. The results indicate that compared with the traditional network caches, with marginal transcoding load, TeC improves the cache effectiveness, decreases the user-perceived latency, and reduces the traffic between the proxy and the content origin server.     

Optimal tree packing for discretized live rate-adaptive streaming in CDN

Rate-adaptive streaming technologies, such as the Dynamic Adaptive Streaming over HTTP (DASH) standard, provides an efficient and easy solution to stream multimedia in a heterogenous context. However, it reinforces the streaming capacity problem in the core Content Delivery Network (CDN) infrastructure since delivering one video means delivering an aggregation of multiple representations. In particular, for live rate-adaptive streaming, a large set of non-divisible data streams need to be either delivered in whole, or not delivered at all. Previous theoretical models that deal with streaming capacity problems are based on elastic bit rates, and do not capture these emerging features faced by today’s CDNs. In this paper, we identify a new, discretized streaming model, for live rate-adaptive video delivery in CDNs. For this model we formulate a general optimization problem and show that it is NP-complete. Then we study two fundamental scenarios that occur in real CDNs. For each of these scenarios, we present a fast, easy to implement, and near-optimal algorithm with performance approximation ratios that are negligible for large networks. These are the first sets of results for the discretized streaming model, and have both practical and theoretical importance in a topic that has become critical.     

Complexity of cloud-based transcoding platform for scalable and effective video streaming services

Nowadays, a fast network improves the quality of our daily life and we can enjoy a variety of services over the Internet. Different types of media streaming services have been proposed and utilized as the network speed is now sufficiently fast to deliver high-quality live streaming. Usually, different media streaming services deliver streaming data by using different protocols such as the real-time message protocol (RTMP), real-time streaming protocol (RTSP), and Windows media HTTP streaming protocol (WMSP). In this paper, we propose and implement a cloud-based scalable and cost-effective video streaming transcoding service platform to provide the service of changing real-time streaming protocols (RTMP/RTSP) and codecs (H.263/H.264). A transcoder dispatching problem (TDP) over the cloud platform is also defined, which attempts to serve all the transcoding requests by minimizing the cost of virtual machines. Further, a transcoder dispatching algorithm and an online transcoder dispatching algorithm are proposed for the TDP. These algorithms are implemented on the Amazon EC2 platform. Experimental results demonstrate that by renting different levels of virtual machines dynamically and intelligently, we can provide a scalable and cost-effective transcoding service for bridging heterogeneous streaming media.