丢包对视频体验质量影响的分析

网络传输过程中发生丢包会降低用户对视频的体验质量。使用EvalVid仿真传输测试床来深入分析丢包率及不同位置丢包对用户体验的影响,并根据回归分析法建立了映射模型。用户使用该模型可以很方便地得出用户的体验质量。经理论分析证明该模型正确、易于操作,可实时检测丢包对视频的影响。     

基于Ip的甚高频传输系统的丢包补偿问题探讨

基于时分复用技术的SDH传输系统中,VHF信号因丢包而造成的语音信号失真现象并不明显.然而,基于IP协议的数据分组交换技术的新一代传输PTN系统,因传输过程中出现的延迟和丢包,会造成大量的音频质量恶化.PTN中采取音频丢包补偿技术对丢失语音数据包进行修复和还原是十分必要的.本文通过具体分析发现引入媒体相关前向差错纠正语音丢包补偿算法.可以较好的解决此类问题,同时兼顾了信号质量和开销间的平衡问题.     

基于QoS量化用户体验质量的评价模型

针对网络环境中业务供应商提供的业务不能很好的满足用户需求的问题,引入用户体验质量（QoE）并结合服务质量（QoS）参数,通过仿真网络得到相应数据,使用matlab工具分别建立用户体验质量与比特率、用户体验质量与丢包率的评价模型.运用统计分析方法对评价模型进行数据分析,并与史蒂文斯幂定律、韦伯-费希纳定律等模型进行对比验证.结果表明,构建的评价模型能更精确的体现用户体验质量与服务质量的关系,为供应商提供了重要的参考依据,并指明了服务方向.     

基于决策树的流媒体视频用户体验质量评测模型研究

文章提出了一种基于决策树的无参考视频用户体验质量评测模型。该模型通过从网络物理层包级别和应用层视频帧级别提取一系列描绘视频特性及网络丢包和时延损伤的特征参数,采用决策树统计学习方法对流媒体服务的用户体验质量进行评测。其中,所有特征参数仅从网络视频数据包的包头部分提取解析,不涉及视频流的解码,从而大大降低了模型的计算复杂度,使评测模型具有独立于视频编码方式的优点。决策树统计学习方法具有分类速度快、可读性高等特点,可以保证实时得到用户体验质量评测结果,同时也可以给出特征参数的相对重要性,为未来的研究工作提供理论依据。实验结果显示,与其他仅考虑单一或部分特征参数的模型相比,同时考虑视频特性及网络丢包和时延损伤的评测模型在预测结果的准确性和一致性方面均有较好的表现。该模型可用于流媒体服务质量实时监控系统。     

一种概率-优先级的分级调度算法研究

在优先级队列调度算法中,队列均需要划分严格的优先级.但考虑到实用网络中,存在着某些队列对时延和丢包要求相近、无法明确区分优先级的情况,提出了一种概率-优先级的分级调度算法:按照队列对时延和丢包的要求进行分组,确定组间的优先级;组内进行基于概率的二级调度;组间进行优先级的一级调度.与优先级队列调度算法相比,该算法保证高优先级数据组的时延性能和丢包性能的同时,整体提高了低优先级数据组的丢包性能.     

低丢包率无线传感器网络S-MAC协议的研究

针对S-MAC协议的层间丢包问题,利用缓存队列原理提出了一种简化通信数据分组格式的S-MAC协议优化改进方案。结合TinyOS的主动消息机制在Mica2节点上实现了改进的S-MAC协议,并对MAC层的丢包率进行了测试。实验测试结果表明,优化改进后S-MAC协议较标准S-MAC协议在MAC层的丢包率上有明显的降低,提高了网络性能。     

基于自适应变速率编码的VoIP网关的研究与应用

针对当前VoIP语音质量易受网络带宽影响的问题,提出了一种基于自适应变速率编码的VoIP网关。通过实时监测RTP语音分组的丢包率,并分析服务质量,自适应地选择最适合当前网络状况的编码速率,以提供一种语音质量和网络状况的最佳组合,从而降低语音分组的丢包率、有效地保障语音服务质量。结合开源项目Asterisk,实现了基于自适应变速率编码的VoIP网关。     

非线性高阶RED拥塞控制算法

针对随机早期检测(RED)算法在网络拥塞不严重的时候丢包率相对较大,而在较严重的时候丢包率相对较小的问题,提出了一种非线性高阶RED拥塞控制算法,目的在于提高算法对网络拥塞的调节能力。该算法建立了一个高阶分组丢弃函数模型,在最小门限值附近丢包率缓慢增长,在最大门限值附近丢包率快速增长,有效地控制了平均队列长度。NS2仿真实验验证了改进算法可有效地提高网络性能。     

基于虚拟分割与自适应图着色的三维模型分组方法

不同于有线网络,无线网络由于信号衰退、信道噪声以及终端节点的移动性导致了数据具有较高的丢包率.为保证三维模型在无线网络中的鲁棒传输,基于交叉思想提出一种针对于压缩三维模型在无线网络传输的分组方法.首先采用阶驱动的方法遍历整个三维模型,并使得每个顶点获得一个全局的遍历索引号;其次提出一种虚拟分割方法将整个模型分成多个片段;再采用提出的自适应图着色算法对每个片段进行遍历,并将片段划分为多个分组;最后从不同的片段中取出分组并按照一定顺序进行组装,形成分组发送序列.实验结果表明,该方法能够促使连续发送分组中的顶点均匀地分散到整个模型中,使得高丢包率无线网络中丢失的顶点能够利用其相邻的未丢失的顶点信息进行恢复,获得较好的重构效果.     

蓝牙室内信道模型与同频干扰研究

蓝牙使用的是免费的ISM频段,容易受到同频段内其它设备的干扰,这些干扰可能来自其他微微网的蓝牙设备。文中分析了蓝牙设备在微微网干扰下的数据传输情况,具体分析了ACL数据分组在微微网同频干扰下的丢包率及吞吐量。为了符合实际的应用场合,给出了适用于蓝牙室内传输的无线传播信道模型。根据室内通信的距离,得出瞬时随机接收信号功率和干扰微微网的随机干扰功率,并根据蓝牙接收特性曲线求出时隙位错误率,然后根据蓝牙不同的数据分组类型求出各分组的平均丢包率和吞吐量。通过分析和仿真可以看出,各ACL数据分组的丢包率和吞吐量基本随通信距离和干扰微微网的数量呈对数下降关系。文中与以往文献相比的特点是：不是一旦发生数据分组“碰撞”就认为丢包,而是由信号和干扰的强度来决定分组是否发送成功。因此分析结果更加准确和实用。     

Packet loss rate mapped to the quality of experience

In order to study the influence of packet loss on the users’ quality of experience QoE and establish the Mapping model of the two when the video transmit in the network, building a NS2?+?MyEvalvid simulation platform, by the method of modifying QoS parameters to simulate different degrees of packet loss, focus on the influence of packet loss on QoE and establish the mapping model between them. Experimental results show that, packet loss has a significant influence on Quality of experience. Packet loss rate and the Quality of experience presents a nonlinear relationship, and use Matlab to establish the mapping model, this model’s accuracy is high, easy to operate, can real-time detect packet loss has influence on the user’s quality of experience (QoE).     

移动视频体验质量的量化评价模型

移动视频体验质量（QoE）的研究正变得日益重要,现有的QoE评价模型缺少相应的量化方法。结合移动视频业务的特点,提出了两层权值的QoE量化评价模型,即QoE由六种“影响层面”按各自的一级权值叠加而成;进一步地,每个“影响层面”又由多个“影响因素”构成。除了丢包和抖动两个“影响因素”外,其他“影响因素”均具有独立的二级权值。提出通过层次分析法（AHP）计算出所有的一级权值,并且进一步计算出除了丢包、抖动外的其他二级权值。由于丢包和抖动这两个影响因素相互依赖,无法计算各自的二级权值,因此通过网络模拟实验,找出两者的双变量函数f（丢包,抖动）,由此得到完整的两层权值QoE量化评价模型。所提QoE量化评价模型通过测评人员的QoE评分进行验证,实验结果表明该模型获得了较高的准确度,证明了上述模型量化方法的可靠性。     

Impact of packet loss on the perceived quality of UDP-based multimedia streaming: a study of user quality of experience in real-life environments

Multimedia content delivery has become one of the pillar services of modern day mobile and fixed networks. The variety of devices, platforms, and content providers together with increasing network capacity has impacted the popularity of this type of service. Considering this context, it is crucial to ensure end-to-end service quality that can fulfill users’ expectations. The user quality of experience (QoE) for multimedia streaming is tempered by numerous objective and subjective parameters; therefore, it is important to understand the relationships among them. In this paper, we thoroughly examine the impact of packet loss on user QoE in cases when multimedia streaming service is based on underlying User Datagram Protocol. The dependencies between the chosen objective and subjective parameters and the user QoE were examined in a real-life environment by conducting a survey with 602 test subjects who rated the quality of a 1-h documentary film (72 different test sequences were prepared for the rating process). Based on the obtained results, we ranked the objective parameters by their order of importance in relation to their impact on user QoE as follows: (1) total duration of packet loss occurrences (PLOs), i.e., quality distortions in a video; (2) number of PLOs; (3) packet loss rate; and (4) duration of a single PLO. We also demonstrated how the overall user experience can be redeemed, despite the perceived quality distortions, if the content is entertaining to the viewer. The user experience was also found to be influenced by the existence/non-existence of video subtitles.     

服务功能链中基于机器学习的QoE评估与预测

在软件定义网络与网络功能虚拟化协同的网络架构下,只考虑单个服务质量（QoS）指标的服务功能链部署无法满足用户的多业务体验需求。提出一种基于机器学习的服务功能链部署模型。基于层次分析法构造MPNQ2算法以建立QoS与体验质量（QoE）的映射关系,得出影响QoE的网络参数并评估其影响权重。在此基础上,利用具备较强综合学习和泛化能力的随机森林模型对服务功能链的QoE进行预测。实验结果表明,与梯度提升决策树、线性判别分析等机器学习模型相比,随机森林模型为预测QoE的最佳模型,同时在影响QoE的网络参数中,丢包率对服务功能链的部署影响最大。     

Impact of video content and transmission impairments on quality of experience

The analysis of the impact of video content and transmission impairments on Quality of Experience (QoE) is a relevant topic for the robust design and adaptation of multimedia infrastructures, services, and applications. The goal of this paper is to study the impact of video content on QoE for different levels of impairments. In more details, this contribution aims at i) the study of the impact of delay, jitter, packet loss, and bandwidth on QoE, ii) the analysis of the impact of video content on QoE, and iii) the evaluation of the relationship between content related parameters (spatial-temporal perceptual information, motion, and data rate) and the QoE for different levels of impairments.     

An ANFIS model of quality of experience prediction in education

This paper presents a Quality of Experience (QoE) prediction model in a student-centered blended learning environment, equipped with appropriate technologically enriched classroom. The model uses ANFIS technique to infer the QoE from the individual subjective factors and the objective technical factors which altogether influence the perceived QoE. We explored the influence of subjective personality traits extroversion and neuroticism, as well as the learning style on QoE. The objective factors included in the model are technically measurable parameters latency, jitter, packet loss and bandwidth affecting Quality of Service (QoS) of the underlying technology. The findings presented in this paper are obtained from a case study which involved 8 teachers and 142 students from second and sixth grade in five primary schools in the Republic of Macedonia. The teachers involved in the project introduced game-based learning strategies in classes, including on-line videoconferences, streamed video content and classical face to face gaming. We constructed three ANFIS systems with seven and four input variables and compared their performances using the RMSE, MAPE and R² measurements. The results showed that perceived QoE can be reliably predicted by the student's personality traits and learning style as subjective factors and network jitter as an objective factor.     

一种视频质量监测系统的设计与实现

网络服务提供商希望能从用户的角度了解目前网络所提供的服务质量,而用户也希望获得定量的指标来评价当前网络服务质量。为此,以视频质量监测为研究对象,提出一种面向用户体验质量的网络监测系统。通过实验分析了网络传输过程中QoS参数对视频QoE的影响;提出一种将视频流转化为测试序列的视频丢包测量方法,该方法能低入侵、准确测量视频传输过程中的丢包情况;基于以上的研究成果,通过对MIB库的扩展和对MIB库轮询机制的研究,构建了面向QoE的视频服务监测系统,该监测系统结构简单、可行性强,实验表明可实时对网络中的视频服务质量进行监测。     

Not All Packets Are Equal, Part I: Streaming Video Coding and SLA Requirements

In this first part of a two-part article, the authors consider the network factors that impact the viewers' quality of experience (QoE) for IP-based video-streaming services such as IPTV. They describe the IP service-level requirements for a transported video service and explain MPEG encoding to help readers better understand the impact that packet loss has on viewers' QoE.