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.     

网络传输中IPTV的QoE评估模型的研究

IPTV是一种基于Internet的多媒体网络服务,由于Internet本身的不可靠性,使其在网络传输过程中无法保证服务质量。为了实时定量评估IPTV服务质量,提出了一种基于IPTV的用户体验评估模型,通过建立从网络服务质量QoS到用户体验质量QoE的映射关系,借助QoS测量技术,以实现针对QoE的在线评估。实验建立IPTV仿真平台,模拟真实网络环境下IPTV媒体流传输的整个过程,实现网络损伤QoS可控和QoE可测。针对不同编码和不同内容的视音频,分别建立独立的QoE评估模型。同时考虑到模型对数据精度和计算速度的需求,给出优化的QoE评估模型。实验结果表明,该评估模型与实际用户体验具有较高的拟合度。     

QoE management for video conferencing applications

We introduce a framework for managing the QoE of videos coded with the H.264 codec and transmitted by video conferencing applications through limited bandwidth networks. We focus our study on the medium-motion videos with QCIF, CIF, and VGA resolutions, the most pervasive video formats used by video conferencing applications across the Internet and cellular telephony systems. Using subjective tests for measuring the level of video quality perceived by end users, we expose the relation between the main influential video parameters and the quality experienced by end users. Furthermore, after investigating the effect of different frame rates and compression levels on video streaming bit rate, and consequently on QoE, we propose a QoE control mechanism for limited-bandwidth situations. A congestion control technique is also introduced in this paper and used in simulations for verifying the efficiency of the proposed QoE management algorithm and to implement this algorithm for practical applications.     

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.     

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).     

移动视频业务QoE自适应测量工具

针对不同无线环境（3G、WiFi）下获取用户体验质量（Quality of Experience,QoE）数据困难和不精确的问题,提出一种基于安卓（Android）移动终端视频业务QoE的自适应测量方法.通过实时测量并评估用户在线视频业务体验质量,提高用户体验质量评价的准确性和实用性.为此开发了能自动测量视频QoE的工具,测量服务质量（Quality of Service,QoS）客观参数,通过效用函数映射到主观QoE（MOS值）.通过对理论QoE评价模型（取自文献）与用户实际反馈相关性研究改进理论模型.结果表明,无线环境下改进的模型测量结果更接近用户实际反馈,可以更好地评价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。     

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.     

HAS QoE prediction based on dynamic video features with data mining in LTE network

Evaluation of HTTP adaptive streaming (HAS) quality of experience (QoE) over LTE network is a challenging topic because of multi-segment and multi-rate features of dynamic video sequences. Different from the traditional QoE evaluation methods based on network parameters, this paper proposes the HAS QoE prediction methods based on its dynamic video segment features with data mining. Considering the application requirement of the trade-off between accuracy and complexity, two sets of methodologies are designed to evaluate the HAS QoE including regression and classification. In regression method, we propose the evolved PSNR (ePSNR) model using differential peak signal to noise ratio (dPSNR) statistics as the segment features to evaluate HAS QoE. In classification method, we propose the improved weighted k-nearest neighbors (WkNN) by using dynamic weighted mapping according to the position of video chunk to meet the dynamic segment and rate features of HAS. In order to train and test these methods, we build a real-time HAS video-on-demand (VOD) system in LTE network and do subjective test in different video scenes. With the mean opinion score (MOS), the regression and classification methods are trained to predict the HAS QoE. The validated results show that the proposed ePSNR and WkNN methods outperform other evaluation methods.     

HTTP移动流媒体QoE管理综述

随着移动通信网络和技术的快速发展,多媒体信息的大量涌现,人们对多媒体信息服务的要求也越来越高。基于HTTP协议的移动流媒体由于拥有广泛运营基础的Web服务器网络环境,部署简单,适用范围广泛等优点成为研究的热点。简要介绍了HTTP移动流媒体的相关特点,重点分析了影响HTTP移动流媒体用户体验质量的各层因素,归纳总结了评价方法和现有的工具,并对 HTTP 移动流媒体相应的优化进行了介绍,最后对HTTP移动流媒体QoE管理进行了总结和展望。     

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.     

基于双向强化学习与动态码率调节的无线mesh网络协议

针对现有无线mesh网络协议的用户体验质量(QoE)较差的问题,提出一种基于双向强化学习与动态码率调节的无线mesh网络协议。首先,设计了兼容不同服务类型的无线mesh网络QoE度量框架;然后,设计了基于双向强化学习的无线mesh网络路由协议;最终,结合QoE感知的差异化报文调度策略与数据流源节点码率动态调节算法进一步优化终端用户的QoE质量。基于NS-2仿真平台的对比实验结果显示,本协议可明显地提高无线mesh网络的QoE指标,同时具有较低的控制开销。     

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。     

流量业务用户感知模型建立及工程化应用

用户感知是终端用户对设备、网络和系统、应用或业务的质量和性能（包括有效性和可用性等方面）的综合主观感受,是终端用户对移动网络提供的业务性能主观感受.它以接近量化的方法来表示终端用户对业务与网络的体验和感受.本文通过层次分析法,建立QoE的评估模型.给出QoE评分的数学公式.并通过一个实例,示范评估过程.     

基于用户偏好的网络质量QoE感知建模仿真分析

为了解决现有网络质量QoE感知模型数据粗差迭代次数多、线性回归参数小的问题,提出基于用户偏好的网络质量QoE感知建模仿真研究。依据用户偏好理论确定模型参数,并获取网络质量QoE感知数据,以此为基础,通过MCD算法判别并去除网络质量QoE数据粗差,以去除粗差的网络质量QoE数据为基础,利用ROI加权算法提取网络质量QoE数据特征,以得到的网络质量QoE数据特征为依据,将其代入多元线性回归方程计算网络质量QoE感知,实现了基于用户偏好的网络质量QoE感知。实验结果显示,与现有三种网络质量QoE感知模型相比较,构建的网络质量QoE感知模型降低了数据粗差迭代次数,提高了线性回归参数,充分说明构建的网络质量QoE感知模型具备更好的性能。     

RTP/I-toward a common application level protocol for distributedinteractive media

Distributed interactive media are media that involve communication over a computer network as well as user interactions with the medium itself. Examples of this kind of media are shared whiteboard presentations and networked computer games. One key problem of this media class is that a large amount of common functionality is currently redesigned and redeveloped for each single medium. In order to solve this problem we present a media model and an application level protocol called RTP/I. Derived from the experience gained with audio and video transmission using RTP, RTP/I is defined as a new protocol framework which reuses many aspects of RTP while it is thoroughly adapted to meet the demands of distributed interactive media. By identifying and supporting the common aspects of distributed interactive media RTP/I allows the reuse of key functionality in form of generic services. Furthermore RTP/I makes it possible for applications of different vendors to interact with each other in a standardized way     

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.     

A survey of data-driven approach on multimedia QoE evaluation

With the development of mobile communication technology and the growth of mobile device, the requirements for user quality of experience (QoE) become higher and higher. Network operators and content providers are interested in QoE evaluation for improving users’ QoE. However, multimedia QoE evaluation faces severe challenges due to the subjective properties of the QoE. In this paper, we provide a survey of the state of the art about applying data-driven approach on QoE evaluation. Firstly, we describe the way to choose factors influencing QoE. Then we investigate and discuss the strengths and shortcomings of existing machine learning algorithms for modeling and predicting users’ QoE. Finally, we describe our research work on how to evaluate QoE in imbalanced dataset.