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。     

丢包对音频流体验质量的影响分析

分组网络中丢包对音频流媒体用户体验具有显著影响,为了深入分析两者间的相关性,设计了丢包可控的多媒体仿真传输实验平台,采用回归分析,建立了编码方式、RTP分组间隔等多因素限定下丢包率与体验质量间的映射模型。该模型计算复杂度低,可实时预测丢包对体验质量的损害。     

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。     

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。     

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。     

MMS业务的QoE定义与测量

用户体验质量已成为移动通信中的一个热门话题,为了有效地测量多媒体短信业务（MMS）的用户体验质量,分析了QoE的定义以及它与传统QoS的区别,介绍了QoE的KQI和KPI之间的相互关系并建立起QoE的映射模型;然后,结合MMS业务的实现流程以及所涉及的网元设备详细定义了MMS业务中的KQIs与KPIs,最后,针对MMS业务提出了一种基于统计样本的QoE测量方案,通过测量明确KPIs与QoE之间的关系以及影响用户体验质量的因素,这对于提高用户的体验质量有重要意义。     

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.     

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.     

Compressed-domain-based no-reference video quality assessment model considering fast motion and scene change

Due to the variability of wireless channel state, video quality monitoring became very important for guaranteeing users’ Quality of Experience (QoE). QoE presents the overall perceptual quality of service from the subjective users’ perspective. However, because of diverse characteristics of video content, Human Visual System (HVS) cannot give the same attention to whole scene simultaneously when facing video sequence. In this paper, we proposed a video quality assessment model by considering the influence of fast motion and scene change. The motion change contribution factor and scene change contribution factor are defined to quantify the characteristics of video content, which is closely related to the users’ QoE. Based on G.1070, our proposed model considers the influential factors of loss nature of video coding, variability of practical network and video features. Also, the proposed model owns low computational complexity due to the compressed domain approach for the estimation of the model parameters. Therefore, the video quality is assessed without fully decoding the video stream. The performance of our proposed model has been compared with five existing models and the results also shown that our model has high prediction accuracy closing to human perception.     

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.     

用户体验质量评估模型及KQI权重计算方法

根据影响用户体验质量(QoE)的技术因素和非技术因素,建立QoE评估模型,以较好地呈现用户主观感受和网络因素。利用该模型提出一种关键质量指标(KQI)权重计算方法,应用模糊层次分析法计算KQI指标初始权重值,并通过影响QoE的非技术因素动态改变KQI指标的权重,使静态QoE评估过程动态化、实时化。仿真实验结果表明,该方法能保证最先假定的技术因素和非技术因素对QoE的影响程度各占50%,较为直观和真实地反映用户感受。     

Multipoint-to-point communications for SHE surveillance with QoS and QoE management

The bandwidth-hunger applications of SHE (Smart Home Environment) can take advantage of the multipoint-to-point (MPP) connections to aggregate more bandwidth to gain user-perceived Quality of Experience (QoE) and network Quality of Service (QoS). The receiver-centric transport-layer R²CP (Radial Reception Control Protocol) was proposed to resolve the incapability of the MPP communication in conventional TCP and UDP. However, R²CP has no consideration to discriminate the importance in a packet payload which is critical to QoE and brings an issue for critical data packets that may be dropped in great risk of network congestion. In this paper, we thus present P-R²CP (Prioritized R²CP) to effectively decrease the loss ratio of critical data packets in MPP video streaming while the network is congested. P-R²CP is a cross-layer protocol that considers both the transport-layer issues and the media content’s properties in application-layer. Then, an example on MPP-UVS (MPP ubiquitous video surveillance) is presented as UVS is now a very important Internet application that requires QoS/QoE management to protect lives and assets especially in SHE. Our experiments are conducted on different kinds of surveillance videos over MPP links with different bandwidth and packet loss inserted. The experimental results demonstrate that, as the loss of critical packets is decreased by an order and much less critical data packets are dropped, P-R²CP can highly guard not only QoS but also QoE of SHE surveillance video streaming.     

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.     

Developing a Quality of Experience (QoE) model for Web Applications

Web‐based service providers have long been required to deliver high quality services in accordance with standards and customer requirements. Increasingly, however, providers are required to think beyond service quality and develop a deeper understanding of their customers' Quality of Experience (QoE). Although models exist that assess the QoE of Web Application, significant challenges remain in: (1) Defining QoE factors from a Web engineering perspective, (2) quantifying the relationship between so‐called “objective” and “subjective” factors of relevance, and (3) dealing with limited data available in relation to subjective factors. In response, the work here presents a novel model (and associated software instantiation) that integrates factors through Key Performance Indicators and Key Quality Indicators. The mapping is incorporated into a correlation model that assesses the QoE of Web Applications, with a consideration of defining the factors in term of quality requirements derived from web architecture. The data resulting from the mapping is used as input of the proposed model to develop artefacts that quantify and predict QoE using Machine Learning. The development of proposed model is framed and guided by Design Science Research approach with the purpose of enabling providers to more informed decisions regarding QoE and/or to optimise resources accordingly. Although the work is oriented at developing an artefact that has clear utility for practice, the nascent design theory underpinning the work is developed and discussed.     

Modeling the influence of network delay on the user experience in distributed home-automation networks

Today’s modern home-automation systems and services (HASS) frequently communicate over public telecommunications networks, such as the Internet. Unfortunately, these communication networks do not usually provide sufficient quality (i.e., a predictable delay), which is generally assured in fieldbus HASS networks. Consequently, the user-perceived quality of experience (QoE) cannot be maintained at a satisfactory level when using different HASS devices communicating over an IP-based network. The data transferred over the Internet can experience a non-negligible delay that can have a considerable influence on the QoE. For this reason, the main goal of our research was to measure the influence of the network delay on a subjective QoE assessment, while interacting with some frequently used HASS tasks. The results show that users are satisfied if the delay is kept below 0.8?s, and that they can tolerate delays of over 2?s (depending on the level of the HASS task interactivity). Since such a user-perceived subjective QoE assessment is both time-consuming and expensive we also propose objective QoE assessment models to represent the influence of network delay on a subjective QoE assessment for various HASS tasks.     

A remote display QoE improvement scheme for interactive applications in low network bandwidth environment

Screen transmission is an essential part of Desktop as a Service (DaaS) which directly influence the quality of experience (QoE). In this paper, we propose a novel QoE improvement scheme that dynamically controls the quality setting of the image compression before the screen transmission to decrease response time of the system still maintaining the satisfactory image quality, hence improves the QoE in interactive applications in a band-limited environment. The proposed scheme first selects the best quality setting appropriate for current network bandwidth quota, then uses the remaining bandwidth to improve the quality setting of low motion regions without any adverse effect on response time. To enable the adaptive quality selection and image quality refinement, we propose a compressed image file size inference model and a block priority calculation method respectively. Particularly, we implement our QoE Improvement Scheme to work with screen content coding. Both quantitative measurements and users’ evaluations in the experiments show that our QoE improvement scheme improves QoS as well as QoE by utilizing the available network bandwidth efficiently.     

QoE assessment model for multimedia streaming services using QoS parameters

This paper proposes a video QoE (Quality of Experience) assessment model which can assess video quality of experience with only QoS (Quality of Service) parameters and their relative importance at network layer. Since network or service providers can forecast whether to provide multimedia services above a certain level of service quality using the proposed model, they can offer and maintain optimum network environment for multimedia service such as IPTV. Through an experiment of video quality comparison we show that our QoS/QoE correlation model is closely related with video quality degradation patterns to network environmental change.     

支持IPTV高清码流连续平滑播放的多级缓冲区设计与实现

把流媒体系统作为一个复杂的控制系统进行研究,给出支持多级反馈控制机制的系统框图,重点分析媒体播放器从流接收到播放的全过程.同时,为了提高用户体验质量,实现音视频流在接收端的连续平滑播放,设计了多级缓冲机制以减少IP网络抖动和丢包产生的影响,实现了根据接收端的解码能力,自适应地选择解码层次和调整帧播放速率.最终采用多线程技术实现了MPEG-2 TS复用H.264高清视频流的解码播放,并给出试验结果.     

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.     

Analysis of Skype VoIP traffic in UMTS: End-to-end QoS and QoE measurements

In the future Internet, multi-network services will follow a new paradigm in which the intelligence of the network control is gradually moved to the edge of the network. This impacts both the objective Quality of Service (QoS) of the end-to-end connection as well as the subjective Quality of Experience (QoE) as perceived by the end user. Skype already offers such a multi-network Voice-over-IP (VoIP) telephony service today. Due to its ease of use and a high sound quality, it becomes increasingly popular in the wired Internet.UMTS operators promise to offer large data rates which should suffice to support VoIP calls in a mobile environment. However, the success of those applications strongly depends on the corresponding QoE. In this work, we analyze the theoretically achievable as well as the actually achieved quality of IP-based voice calls using Skype. This is done performing measurements in both a real UMTS network and a testbed environment. The latter is used to emulate rate control mechanisms and changing system conditions of UMTS networks. The results show in how far Skype over UMTS is able to keep pace with existing mobile telephony systems and how it reacts to different network characteristics. The investigated performance measures comprise the QoE in terms of the MOS value and the QoS in terms of network-based factors like throughput, packet interarrival times, or packet loss.