一种融合用户偏好和社交活跃度的推荐算法

为有效解决传统推荐算法精度低的问题,提出了一种融合用户偏好和社交活跃度的概率矩阵分解推荐算法(Probabilistic Matrix Factorization Recommendation Algorithm Combining User Prefer-ence and Social Activity,UPSA-PMF),通过用户评分数据计算用户间的偏好信任度时,使用了共同项目平衡因子和热门项目惩罚因子进行改进;计算社交网络中的信任度时,考虑了社交活跃度与用户信任度的关系,并将社交活跃度作为惩罚因子,修正用户信任度.将偏好信任度和社交网络中的信任度以动态组合的方式得到最终的信任度,将最终的信任度与概率矩阵模型相结合,实现推荐.实验证明,改进的算法均优于现有的推荐算法,有效提高了推荐质量.     

移动视频源m3u8多码率节目源终端自动适配技术

高速的网络环境为OTT互联网电视用户带来了更好的体验,也增加了个性化及多样性的需求.文中提出了根据用户终端网络带宽自适应匹配最优视频源码率的方案,根据用户家庭子网带宽和网络环境,终端自适应匹配最优节目源码率,有效提升用户视频播放及体验,保障在差异化网络环境条件下,为用户提供最优服务.     

基于电视的社交化通信应用解决方案及关键技术研究

详细探讨和介绍了基于电视部署社交化多媒体通信业务的策略,提出与现网结合进行系统部署的方案.为了有效提升电视上的社交体验和通信质量,对屏幕应用适配、视频叠加、实时视频编解码、视频质量自适应等关键技术进行了研究与分析.最后通过实验室测试,验证了本方案在现网应用的可行性.     

单码流场景下P2P流媒体直播数据调度方法

由于具有较高应对节点动态性的能力和较强的扩展性,Mesh-Pull P2P流媒体直播分发方法赢得了学术界和工业界的广泛青睐.提出了传统互联网单码流场景下Mesh-Pull P2P流媒体直播的数据调度算法.该算法采用TOPSIS方法来解决调度算法中数据块优先级的量化这一多属性决策问题,以降低节点的启动延迟.仿真实验表明,本算法可以在保证高视频播放质量的情况下降低用户观看视频的延迟.     

互联网电视业务质量保障及用户体验检测

互联网电视业务通过宽带网络给用户提供交互式多媒体服务,它加快了三网融合的发展。本文首先从互联网电视业务用户体验入手,讨论了其服务质量保障的必要性;其次分别研究了针对互联网电视的视频质量分析模型和质量保障方案,给出了利用MOS值来分析视频质量的过程,并介绍了系统的质量监测系统。最后根据网络视频传输过程中获得的参数,利用模糊逻辑估计用户体验MOS值。     

社交:互联网电视的新标签

尽管产业各方都对社交电视表现出了浓厚兴趣,然而整体来看,社交电视仍处于概念讨论阶段。"社交电视能够为用户提供全新的互联网电视体验,我们认为这是互联网电视一个有前景的方向,南方传媒集团也将大力支持和积极推进社交电视发展。——南方传媒集团总工程师夏倜"     

视频用户体验理论与实践

随着视频服务逐渐成为人们获取信息的主要途径之一,消费者对观看体验的要求不断提高,视频用户体验质量已经成为视频服务的主要竞争因素.首先对用户体验质量理论进行了系统的阐述,指出了用户体验质量与服务质量之间的差别和联系,同时给出了用户体验评价方法的主要步骤和视频质量评价的具体方法.进一步地,对我国现阶段视频用户体验评价研究及标准化的进展进行详细介绍,概括了目前我国视频服务的用户体验现状并给出了相关的改进方向意见.     

基于Q学习的异构无线网络动态切换策略

提出了一种基于Q学习的动态切换策略,用于最大化用户体验(QoE).基于Q学习的动态切换策略选择最佳网络,不仅利用当前网络状态还利用了未来网络状态和用户终端状态.不同于其他动态规划算法,该算法不需要获取无线网络环境的信息,而是通过利用用户终端过去经验来学习最优策略.仿真结果显示,该动态切换策略能以较少网络间切换次数来接近甲骨文优化算法性能,从而使用户体验得到更优质的网络音频服务.     

基于P2P流媒体直播系统的数据传输策略

针对P2P模式下视频流媒体直播系统的数据传输策略用改进的模拟退火算法进行了优化。以全局规划的思想建立了P2P视频流媒体的数据传输策略数学模型VMDTSA-P2P,模型充分考虑了可用出口带宽和可用性时间对播放连续性的影响,把它们作为获取最优解的目标函数因子,并用改进后的模拟退火算法进行解的寻优,相比于传统的数据传输策略,在具有大量用户的情况下加快了新节点从伙伴节点中选择数据块提供节点的速度,并且保证得到近似最优的数据块提供节点组合,减少了视频流媒体直播系统播放的延迟,从而提高了播放的连续性、流畅性,保证了视频播放的质量。通过该算法在模拟P2P系统中的实现,验证了该算法在P2P系统中对数据传输的准确性和高效性。     

USB传输视频的实现与比较

上升中的USB3.0会在视频传输领域扮演一个角色,但至少要与两个接口竞争者分享:HDMI和Display Port。这三个标准各有优点,都有资本占据数字起居室、PC和移动电子空间。HDTV(高清晰电视)改变了消费者对数字媒体体验的预期,从而永远改变了世界。现在,内容的创建与消费都达到了一个转折点;人们不再满足于只观看电视节目和一流高清质量的电影。今天,连接到一些社交媒体上的用户有6亿以上,用户产生的     

Scalable video transmission over multi-hop wireless networks with enhanced quality of experience using swarm intelligence

In this work, we take the advantages of the particle swarm optimization method which belongs to the family of swarm intelligence algorithms to find improved solutions for delivering digital video content with enhanced quality of experience to the end users over error-prone multi-hop wireless networks. In video transmission over such wireless networks, many network-based (packet loss, delay, etc.) and source-based (encoding quantization level, etc.) parameters can impair the perceived video quality. The main contributions of the proposed work are twofold. At first, an optimal bandwidth allocation framework is being developed based on the particle swarm optimization algorithm in which by incorporating an accurate video quality metric, the total weighted quality of experience of some competing video sources is being optimized. Secondly, these optimal rates have been used for differentiated quality of experience enforcement between multiple competing scalable video sources. The resulting optimal rates can be used as rate-feedbacks for on-line rate adaptation of a moderate scalable video encoder such as H.264/MPEG4 AVC. The aforementioned weight parameters are selected based on the importance of each video sequence's quality and can be associated with some previous service level agreement based prices. Some guidelines about the practical implementation of the proposed algorithm are given. Numerical analysis has been performed to validate the theoretical results and to verify the claims.     

面向蜂窝网络的D2D多播通信的分簇和中继选择方法

传统蜂窝网络中,信道衰减的随机性和不确定性导致小区边缘用户的接收性能很差,尤其是面向视频传输等速率要求较高时其弊端更加凸显。D2D通信因其配置灵活性可作为传统蜂窝网络架构的有利补充,能有效改善边缘用户的性能。该文针对D2D通信的多播传输,分析了系统最小时延成本下的中继数量和分簇算法,提出一种基于分簇和中继选择的低时延D2D多播方案。该方案可以自适应选择多播重传中的中继的数量和中继节点到基站的距离,同时给出最优的带宽资源分配机制。仿真结果表明,与其他方案相比,所提方法能有效减少系统时延,提高边缘用户体验和系统性能。     

QoE-aware mobile IPTV channel control algorithm over WiMAX network

In this paper, we present an effective IPTV channel control algorithm that improves the quality of experience for subscribers to mobile IPTV services over WiMAX network. We consider the video quality of TV channels and the channel zapping time as quality of experience metrics. The proposed algorithm controls the channel distribution state and the target bit rate of TV channels based on the channel preference information of subscribers to achieve an effective trade-off between channel zapping time and video quality. Finally, simulation results are provided to demonstrate the performance of the proposed system.     

Quality-driven cross-layer optimized video delivery over LTE

3GPP Long Term Evolution is one of the major steps in mobile communication to enhance the user experience for next-generation mobile broadband networks. In LTE, orthogonal frequency- division multiple access is adopted in the downlink of its E-UTRA air interface. Although cross-layer techniques have been widely adopted in literature for dynamic resource allocation to maximize data rate in OFDMA wireless networks, application-oriented quality of service for video delivery, such as delay constraint and video distortion, have been largely ignored. However, for wireless video delivery in LTE, especially delay-bounded real-time video streaming, higher data rate could lead to higher packet loss rate, thus degrading the user-perceived video quality. In this article we present a new QoS-aware LTE OFDMA scheduling algorithm for wireless real-time video delivery over the downlink of LTE cellular networks to achieve the best user-perceived video quality under the given application delay constraint. In the proposed approach, system throughput, application QoS constraints, and scheduling fairness are jointly integrated into a cross-layer design framework to dynamically perform radio resource allocation for multiple users, and to effectively choose the optimal system parameters such as modulation and coding scheme and video encoding parameters to adapt to the varying channel quality of each resource block. Experimental results have shown significant performance enhancement of the proposed system.     

基于云服务的电视实现方法研究

该文所述基于云服务的电视实现方法,是基于云计算的一种新颖的电视接人、视频内容分发的方法。此方法有别于目前基于互联网传送的各类智能电视,而是针对互联网云计算的商业模式,彻底解决互联网电视操作复杂、成本高的问题。该文提出的是一种不内置嵌入式计算机平台、不内置web浏览器,以及用户任务推送器,仅基于云服务的用户接入管理服务器来接人云端,采用虚拟显示技术的新颖云电视机技术,从而完成电视机与媒体资源之间的传递。     

A simplified deniable authentication scheme in cloud‐based pay‐TV system with privacy protection

Cloud computing is a milestones for computing model, which enables on‐demand, flexible, and low‐cost usage of computing resources, especially for cloud storage. Nowadays, the services of cloud‐based pay‐TV systems are emerging endlessly. But these pay‐TV systems' privacy is not given enough attention. The users not only care about their information revealed during transmission processes but are also concerned about whether the video contents that they have seen were recorded by the pay‐TV systems or not. In this work, I propose a novel deniable authentication protocol in a cloud‐based pay‐TV system, named DAP‐TV, aiming to achieve mutual authentication, deniability, and privacy protection in cloud‐based pay‐TV systems. The unique feature of our scheme is deniability which means a pay‐TV system to identify a user is a legal user, but the pay‐TV system cannot prove video contents that the user has seen to any third party over an unsecured network. In additon, our scheme is based on chaotic maps, which is a highly efficient cryptosystem and is firstly used to construct a deniable authentication scheme in pay‐TV systems. Finally, we give the formal security proof and efficiency comparison with recently related works.     

移动边缘计算中基于联邦学习的视频请求预测和协作缓存策略

随着互联网社交平台的崛起和移动智能终端设备的普及,自媒体短视频、直播等视频业务蓬勃发展,人们对高质量视频服务的需求也急剧上升。与此同时,连接到核心网络的大量智能设备增加了回程链路的负载,传统的云计算难以满足用户对视频服务的低延迟要求。移动边缘计算(MEC)通过在网络边缘部署具有计算和存储能力的边缘节点,通过在更靠近用户的边缘侧提高计算和存储服务,降低了数据传输时延进而缓解了网络阻塞。因此,基于MEC架构,该文充分利用网络边缘资源,提出了基于联邦学习的视频请求预测和视频协作缓存策略。通过利用多个边缘节点对提出的深度请求预测模型(DRPN)视频请求预测模型进行联邦训练,预测视频未来的请求情况,然后量化缓存内容所带来的时延收益并协作地以最大化该时延收益为目的进行缓存决策。该文分析了真实数据集MovieLens,模拟了视频请求缓存场景并进行实验。仿真结果表明,相比于其他策略,所提策略不仅能有效降低用户等待时延,在有限的缓存空间中提高内容多样性,从而提高缓存命中率,降低缓存成本,还能降低整个系统的通信成本。     

Impact of VNF placements on QoE monitoring in the cloud

The fast growth of video streaming is responsible for a huge amount of traffic over the past few years. Because of the variety of video content on the Internet, a potential market is emerging for video providers. However, a rapid increase in video traffic and users poses challenges for network operators maintaining user expectation. To address this problem, network operators need a mechanism to monitor the quality of experience (QoE) perceived by the user. This allows reacting to quality degradation to improve the service. With the paradigm of network function virtualization, network operators are able to deploy such a video monitoring function in the cloud. In this work, we investigate the feasibility of deploying a virtual network function (VNF) for video buffer and QoE monitoring on the Amazon Web Service cloud. To this end, we implement a VNF to analyze video flows in the network by using deep packet inspection. We investigate the influence of different points of presence (PoP) in the cloud and mobile network on the performance of the VNF for monitoring video buffer and QoE. Our findings show that the accuracy of the QoE monitoring decreases with the distance of the PoP to the client. This is not only due to the delay and bottleneck between the monitoring point and the client but also due to the client mobile access network.     

时延约束下采用SVC编码的D2D协作视频多播传输方案

为缓解基站的视频流量过载，本文针对时延敏感的实时视频业务，设计一种D2D协作视频多播传输方案。该方案采用可伸缩视频编码（Scalable Video Coding, SVC）对视频流进行编码处理，利用SVC流的分层结构特征来应对多播信道间的差异性。在SVC编码的基础上，为了改善用户观看体验及提升用户所接收的视频质量，所提出的协作式视频传输方案引入有效吞吐量这一概念，在一定时延约束下，根据信道反馈信息灵活地对不同信道上的不同SVC视频层进行码率调整。仿真结果表明，所提出的方案能够有效地减小端到端时延，有效丢失率，提高有效吞吐量。      

Rate control for consistent visual quality of H.264/AVC encoding

In this paper, a novel rate control scheme with sliding window basic unit is proposed to achieve consistent or smooth visual quality for H.264/AVC based video streaming. A sliding window consists of a group of successive frames and moves forward by one frame each time. To make the sliding window scheme possible for real-time video streaming, the initial encoder delay inherently in a video streaming system is utilized to generate all the bits of a window in advance, so that these bits for transmission are ready before their due time. The use of initial encoder delay does not introduce any additional delay in video streaming but benefits visual quality as compared to traditional one-pass rate control algorithms of H.264/AVC. Then, a Sliding Window Buffer Checking (SWBC) algorithm is proposed for buffer control at sliding window level and it accords with traditional buffer measurement of H.264/AVC. Extensive experimental results exhibit that higher coding performance, consistent visual quality and compliant buffer constraint can be achieved by the proposed algorithm.