基于HLS的流媒体播放系统的设计与实现

HTTP Live Streaming（简称HLS）是苹果公司提出的移动流媒体协议,广泛应用于传统和移动互联网多媒体应用.在对HTTP Live Streaming协议进行研究的基础上,结合HTML5一些新的特性,给出了一种在iOS设备上基于HTTP Live Streaming的流媒体播放系统的部署方案.结合实际部署的效果,探讨了该协议的特点和当前情况下存在的一些不足.     

Adaptive video streaming testbed design for performance study and assessment of QoE

Hypertext Transfer Protocol adaptive streaming switches between different video qualities, adapting to the network conditions, and avoids stalling streamed frames over high‐oscillation client's throughput improving the users' quality of experience (QoE). Quality of experience has become the most important parameter to lead the service providers to know about the end‐user feedback. Implementing Hypertext Transfer Protocol adaptive streaming applications to find out QoE in real‐life scenarios of vast networks becomes more challenging and complex task regarding to cost, agile, time, and decisions. In this paper, a virtualized network testbed to virtualize various machines to support implementing experiments of adaptive video streaming has been developed. Within the test study, the metrics which demonstrate performance of QoE are investigated, respectively, including initial delay (ie, startup delay at the beginning of playback a video), frequency switches (ie, number of times the quality is changed), accumulative video time (ie, number and length of stalls), CPU usage, and battery energy consumption. Furthermore, the relation between effective parameters of QoS on the aforementioned metrics for different segment length is investigated. Experimental results show that the proposed virtualized system is agile, easy to install and use, and costs less than real testbeds. Moreover, the subjective and objective performance studies of QoE evaluation in the system have proven that the segment lengths of 6 to 8 seconds were faired and more efficient than others according to the investigated parameters.     

Impact of playout buffer dynamics on the QoE of wireless adaptive HTTP progressive video

The quality of experience (QoE) of video streaming is degraded by playback interruptions, which can be mitigated by the playout buffers of end users. To analyze the impact of playout buffer dynamics on the QoE of wireless adaptive hypertext transfer protocol (HTTP) progressive video, we model the playout buffer as a G/D/1 queue with an arbitrary packet arrival rate and deterministic service time. Because all video packets within a block must be available in the playout buffer before that block is decoded, playback interruption can occur even when the playout buffer is non-empty. We analyze the queue length evolution of the playout buffer using diffusion approximation. Closed-form expressions for user-perceived video quality are derived in terms of the buffering delay, playback duration, and interruption probability for an infinite buffer size, the packet loss probability and re-buffering probability for a finite buffer size. Simulation results verify our theoretical analysis and reveal that the impact of playout buffer dynamics on QoE is content dependent, which can contribute to the design of QoE-driven wireless adaptive HTTP progressive video management.     

Incentive analysis for cooperative interactive multiview video streaming

In interactive multiview video streaming (IMVS), users can periodically select one out of many captured views available for observation. In single-view video streaming, cooperative strategies where peers share received packets of the same video have proven to be effective in reducing server׳s upload burden, and incentive mechanisms are designed to stimulate user cooperation. However, exploiting user cooperation in higher dimensional IMVS is difficult, since users watching different views makes it difficult to establish partnership, and users switching views frequently and independently makes it difficult to maintain partnership over time. In this paper, we use a multiview video frame structure for IMVS to support cooperative view-switching, where peers may help each other even if they are observing different views. We then model peers׳ interaction as an indirect reciprocity game, where each user is assigned a reputation level. To gain a higher reputation level, users help others, which in turn leads to a higher likelihood to receive others׳ help later. In this work, we focus on how view switching, the key feature of IMVS, affects user cooperation. By modeling users׳ decision making as a Markov decision process, our analysis shows that users tend to cooperate at some views but not others: given peers can predict their future view navigation paths probabilistically, for a peer who is likely to enter a view-switching path not requiring others׳ help, he also has less incentive to cooperate. Furthermore, we observe that the game may have multiple Nash Equilibria corresponding to different cooperation levels, e.g., users cooperate at all views in the full cooperation equilibrium, while users only cooperate at certain views in the partial cooperation equilibrium. The particular equilibrium the game will converge to depends on the initial cooperation level of the game. To stimulate user cooperation at all views, we propose a Pay-for-Cooperation (PfC) scheme at the beginning of the game to drive the game to the full cooperation equilibrium to improve system efficiency. Our simulation results show the effectiveness of PfC.     

Research on Q-learning based rate control approach for HTTP adaptive streaming

HTTP adaptive streaming (HAS) has become the standard for adaptive video streaming service.In changing network environments,current hardcoded-based rate adaptation algorithm was less flexible,and it is insufficient to consider the quality of experience (QoE).To optimize the QoE of users,a rate control approach based on Q-learning strategy was proposed.the client environments of HTTP adaptive video streaming was modeled and the state transition rule was defined.Three parameters related to QoE were quantified and a novel reward function was constructed.The experiments were employed by the Q-learning rate control approach in two typical HAS algorithms.The experiments show the rate control approach can enhance the stability of rate switching in HAS clients.     

A QoE centric distributed caching approach for vehicular video streaming in cellular networks

Distributed caching‐empowered wireless networks can greatly improve the efficiency of data storage and transmission and thereby the users' quality of experience (QoE). However, how this technology can alleviate the network access pressure while ensuring the consistency of content delivery is still an open question, especially in the case where the users are in fast motion. Therefore, in this paper, we investigate the caching issue emerging from a forthcoming scenario where vehicular video streaming is performed under cellular networks. Specifically, a QoE centric distributed caching approach is proposed to fulfill as many users' requests as possible, considering the limited caching space of base stations and basic user experience guarantee. Firstly, a QoE evaluation model is established using verified empirical data. Also, the mathematic relationship between the streaming bit rate and actual storage space is developed. Then, the distributed caching management for vehicular video streaming is formulated as a constrained optimization problem and solved with the generalized–reduced gradient method. Simulation results indicate that our approach can improve the users' satisfaction ratio by up to 40%. Copyright © 2015 John Wiley & Sons, Ltd.     

QoE optimization for HTTP adaptive streaming: Performance evaluation of MEC-assisted and client-based methods

Seamless streaming of high quality video under unstable network condition is a big challenge. HTTP adaptive streaming (HAS) provides a solution that adapts the video quality according to the network conditions. Traditionally, HAS algorithm runs at the client side while the clients are unaware of bottlenecks in the radio channel and competing clients. The traditional adaptation strategies do not explicitly coordinate between the clients, servers, and cellular networks. The lack of coordination has been shown to lead to suboptimal user experience. As a response, multi-access edge computing (MEC)-assisted adaptation techniques emerged to take advantage of computing and content storage capabilities in mobile networks. In this study, we investigate the performance of both MEC-assisted and client-side adaptation methods in a multi-client cellular environment. Evaluation and comparison are performed in terms of not only the video rate and dynamics of the playback buffer but also the fairness and bandwidth utilization. We conduct extensive experiments to evaluate the algorithms under varying client, server, dataset, and network settings. Results demonstrate that the MEC-assisted algorithms improve fairness and bandwidth utilization compared to the client-based algorithms for most settings. They also reveal that the buffer-based algorithms achieve significant quality of experience; however, these algorithms perform poorly compared with throughput-based algorithms in protecting the playback buffer under rapidly varying bandwidth fluctuations. In addition, we observe that the preparation of the representation sets affects the performance of the algorithms, as does the playback buffer size and segment duration. Finally, we provide suggestions based on the behaviors of the algorithms in a multi-client environment.     

Design and Implementation of a Network‐Adaptive Mechanism for HTTP Video Streaming

This paper proposes a network‐adaptive mechanism for HTTP‐based video streaming over wireless/mobile networks. To provide adaptive video streaming over wireless/mobile networks, the proposed mechanism consists of a throughput estimation scheme in the time‐variant wireless network environment and a video rate selection algorithm used to increase the streaming quality. The adaptive video streaming system with proposed modules is implemented using an open source multimedia framework and is validated over emulated wireless/mobile networks. The emulator helps to model and emulate network conditions based on data collected from actual experiments. The experiment results show that the proposed mechanism provides higher video quality than the existing system provides and a rate of video streaming almost void of freezing.     

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。     

Eliminating bandwidth estimation from adaptive video streaming in wireless networks

Dynamic Adaptive Streaming over HTTP (DASH) is the state-of-the-art technology for video streaming and has been widely deployed in both wired and wireless environments. However, mobile DASH users often suffer from video quality oscillation and even video freeze in wireless environments, which results in poor user experience. This is mainly because most quality adaptation algorithms in DASH rely highly on bandwidth estimation to adjust the video quality while wireless network bandwidth is unstable in nature and changes frequently according to wireless channel contention and condition. To provide stable performance, even during severe bandwidth fluctuation, this paper proposes the Wireless Quality Adaptation (WQUAD) algorithm, which eliminates bandwidth estimation from quality adaptation. Thanks to the Scalable Video Codec (SVC), the proposed scheme always prioritizes to lower layers over higher ones as long as the play-out buffer is not completely filled by the lower layers. As a result, the client always fills the buffer with the base layers first and then the upper enhancement layers sequentially. This horizontal adaptation is straightforward and does not require any bandwidth estimation. Through NS-2 simulations, we show that WQUAD achieves (i) stable performance, keeping the video quality level with respect to the long-term network bandwidth, (ii) effective video freeze prevention, and (iii) high video quality on average.     

对主流自适应码率流媒体技术的分析

伴随着互联网多媒体应用的快速增长,尤其是在线视频业务的不断发展,传统的流媒体技术由于其单一的编码方式难以适应差异化的用户网络变化,极大地影响了用户体验。分析了当前在线视频业务面临的主要问题,同时介绍了新兴的自适应码率流媒体技术的特点和优势。通过对主流自适应码率流媒体和传统流媒体技术的分析和比较,表明对于OTT业务而言,标准化的自适应码率流媒体技术比传统的流媒体技术更加有优势。     

基于视频大数据的用户画像构建

为了能更加高效地发挥用户在跨平台收视中产生的视频大数据资产,充分挖掘视频大数据中潜在的用户基础信息和行为偏好,基于大数据构建用户画像在视频领域的应用越来越广泛.首先阐述了用户画像的基本概念、构建原则以及在相关领域的应用.然后对视频大数据进行了深度剖析,对视频大数据的界定以及视频大数据的应用进行了阐述.接着阐述了基于视频大数据进行用户画像构建的基本步骤,从数据源、标签和权重、数据建模以及数据可视化层面对用户画像的搭建进行了深度介绍.最后介绍了用户画像在视频领域的应用案例,由于用户画像的应用相当广泛,着重从个性化推荐和精准营销两个层面介绍了用户画像在视频领域的应用案例.     

基于OpenFlow的SVC流媒体时延自适应分级传输方法

针对当前互联网流媒体传输的时延敏感性问题,提出一种基于OpenFlow的SVC（scalable video coding,可分级视频编码）流媒体时延自适应分级传输方法,该方法有效结合SVC流媒体可分级和OpenFlow灵活可编程的特性,在网络带宽受限和链路拥塞的复杂网络环境下,通过构建基础层和增强层2个独立路由,实现了动态网络下SVC流媒体分级自适应高效传输。仿真结果表明,该方法在提升SVC流媒体传输效率和质量,改善用户体验方面有重要作用。     

虚拟现实视频处理与传输技术

虚拟现实(VR)是当前视频领域研究热点.介绍了VR视频内容制作以及终端显示技术现状,分析了基于用户视点的VR视频处理关键技术,最后探讨了VR视频传输模式及其对承载网络的需求.     

多Agent协作可交互的远程视频会议系统的实现

为了使身处不同场所的人可以参与同一场会议,并且可以自由发言和讨论,设计实现了基于多Agent协作的可交互的远程视频会议系统.首先采用了FEC前向纠错和树形P2P技术,搭建起直播会场架构,传输音视频数据,然后通过申请成为互动焦点让分会场端可参与发言讨论,最后引入多Agent协作技术,提高系统稳健性.实验表明,正常网络情况下,该系统能支持350分会场同步直播,音视频质量流畅,可以很好地开展大型远程视频会议.     

交互式视频编辑的设计与实现

随着社会经济的不断发展,影音成像等各种媒体事业也取得了空前的发展,视频编辑在艺术传播和影音技术发展方面起到不可或缺的作用.针对当前影音技术发展的势头,能够进一步地完善视频编辑系统的体系,实现交互式视频编辑的设计,对当今影音技术的发展起到相当程度上的推动作用.     

基于HTTP协议的服务器程序分析

绝大多数的Web开发,都是构建在HTTP协议之上的Web应用。为了分析基于HTTP协议服务器程序以及浏览器与服务器的交互过程,以一个简单的基于HTTP协议中服务器程序为实例,探讨怎样使用多线程与异步操作的理论,运用WinSock编程来逐步解析HTTP协议的服务器程序的核心部分,这样既可达到避免调用线程阻塞的目的,又可提高服务器程序的可响应性。     

On quality of experience of scalable video adaptation

In this paper, we study the quality of experience (QoE) issues in scalable video coding (SVC) for its adaptation in video communications. A QoE assessment database is developed according to SVC scalabilities. Based on the subjective evaluation results, we derive the optimal scalability adaptation track for the individual video and further summarize common scalability adaptation tracks for videos according to their spatial information (SI) and temporal information (TI). Based on the summarized adaptation tracks, we conclude some general guidelines for the effective SVC video adaptation. A rate-QoE model for SVC adaptation is derived accordingly. Experimental results show that the proposed QoE-aware scalability adaptation scheme significantly outperforms the conventional adaptation schemes in terms of QoE. Moreover, the proposed QoE model reflects the rate and QoE relationship in SVC adaptation and thus, provides a useful methodology to estimate video QoE which is important for QoE-aware scalable video streaming.     

3D visual experience oriented cross-layer optimized scalable texture plus depth based 3D video streaming over wireless networks

3D video streaming over the mobile Internet generally incurs the inferior 3D visual experience due to the time-varying characteristics of wireless channel. The conventional video streaming optimization methods generally neglect the harmony among different networking protocol layers. This paper proposes a cross-layer optimized texture plus depth based scalable 3D video streaming method to improve the expected 3D visual experience of the user by systematically considering the application layer texture-video/depth/FEC bit-rate allocation, MAC layer multi-channel allocation, and physical layer modulation and channel coding scheme (MCS) selection. In the cross-layer optimization, a networking-related 3D visual experience model which fuses the overlapped retinal view visual quality and depth sensation with mimicking human vision system is established to predict the 3D visual experience under the specific parameter configurations of different protocol layers. The efficiency and effectiveness of the proposed cross-layer optimized 3D video streaming method has been validated by subjective and objective experimental results.     

Impact of viewer engagement on gift-giving in live video streaming

This study investigates the effect of viewer engagement on gifting items to a streamer in a live video streaming. Data were collected from AfreecaTV, a leading live video streaming platform in South Korea, to examine viewer engagement and gift-giving behavior. After analyzing 2,294,837 viewers over a three-month period, the empirical results provide evidence that viewer engagement is positively associated with gift-giving decisions. However, the impact of viewer engagement on the amount of gifts purchased is different depending on how the engagement is measured (i.e., by stream or by channel). This study empirically proves that the motive for socialization has a high correlation with gift-giving behavior, which is considered as commoditization of a viewer’s social interaction while consuming media. The study concludes with a discussion on practical implications for live video streaming services and suggestions for future research.