Quality of experience evaluation of HTTP video streaming based on user interactive behaviors

User interactive behaviors play a dual role during the hypertext transfer protocol (HTTP) video service: reflection and influence. However, they are seldom taken into account in practices. To this end, this paper puts forward the user interactive behaviors, as subjective factors of quality of experience (QoE) from viewer level, to structure a comprehensive multilayer evaluation model based on classic network quality of service (QoS) and application QoS. First, dual roles of user behaviors are studied and the characteristics are extracted where the user experience is correlated with user interactive behaviors. Furthermore, we categorize QoE factors into three dimensions and build the metric system. Then we perform the subjective tests and investigate the relationships among network path quality, user behaviors, and QoE. Ultimately, we employ the back propagation neural network (BPNN) to validate our analysis and model. Through the simulation experiment of mathematical and BPNN, the dual effects of user interaction behaviors on the reflection and influence of QoE in the video stream are analyzed, and the QoE metric system and evaluation model are established.     

Q2ABR: QoE‐aware adaptive video bit rate solution

In this paper, we propose a new adaptive bit rate (ABR) streaming method. This method is based on estimating and monitoring users' video streaming experience, their quality of experience (QoE). This ensures a good user QoE and optimises bandwidth utilisation by monitoring video buffer fill rate to ensure minimal data traffic. First, we achieve a QoE evaluation model based on network bandwidth, video segment representation, and dropped video frame rate parameters. Second, following our QoE evaluation model, we formulate an ABR method using the reinforcement learning (RL) paradigm to select video representations and using a breakpoint detection mechanism to monitor end‐user QoE variation. The proposed ABR method is called “QoE‐aware adaptive bit rate (Q2ABR)” and is composed of three individual modules, one for QoE estimation using machine learning methods, one for QoE variation monitoring using the breakpoint detection mechanism, and one for video representation selection using reinforcement learning. The design objective of Q2ABR is to ensure the overall QoE of these users while maintaining a minimum variation in the standard deviation of the users' QoE values. Third, the performance of the Q2ABR method is evaluated and compared with several existing ABR approaches in the literature using real traces that we collect on different transport scenarios (such as bus and train, among others). Since this method considers the user's perception of video quality as a regulator for optimising the overall video distribution network, good results are ensured in terms of the user's experience and buffer fill rate.     

QoE‐based pseudo heartbeat message compression mechanism for future wireless network

Wireless multimedia services are increasingly becoming popular, which boosts the need for better quality‐of‐experience (QoE). However, there are many aspects leading to the degradation of real‐time video QoE, especially, a large number of always‐on‐line (AOL) applications existing in future wireless networks transmit heartbeat message periodically to keep always‐on, and hence induce heavy signaling costs and overload wireless networks. In this paper, we propose QoE‐based pseudo heartbeat message compression mechanism to reduce the number of signaling loads in the radio access network by intercepting the heartbeat message at a certain frequency in the proxy client. To maintain the protocol feature of the AOL applications, the heartbeat messages are reconstructed by the proxy server and sent to the application server. Furthermore, to analyze the influence of this mechanism on the video user, a new QoE perception model is proposed. Finally, combined the QoE perception model for video services with AOL services, the utility function for joint optimization multi‐services is developed to determine the optimum compression frequency. The simulation results show that the proposed mechanism greatly alleviates the signaling load and leads to a significant performance improvement on the QoE of video users, while a slight decrease in the QoE of AOL users. Copyright © 2016 John Wiley & Sons, Ltd.     

Proposed Framework for Evaluating Quality of Experience in a Mobile,Testbed-oriented Living Lab Setting

The framework presented in this paper enables the evaluation of Quality of Experience (QoE) in a mobile, testbed-oriented Living Lab setting. As a result, it fits within the shift towards more user-centric approaches in innovation research and aims to bridge the gap between technical parameters and human experience factors. In view of this, Quality of Experience is seen as a multi-dimensional concept, which should be considered from an interdisciplinary perspective. Although several approaches for evaluating perceived QoE have been proposed in the past, they tend to focus on a limited number of objective dimensions and fail to grasp the subjective counterparts of users’ experiences. We therefore propose a distributed architecture for monitoring network Quality of Service (QoS), context information and subjective user experience based on the functional requirements related to real-time experience measurements in real-life settings. This approach allows us to evaluate all relevant QoE-dimensions in a mobile context.     

Slicing Wi-Fi links based on QoE video streaming fairness

Dynamic Adaptive Streaming over HyperText Transfer Protocol (DASH) video streaming is one of the dominant sources of traffic on the Internet, and this traffic is often delivered to users via Wi-Fi access points. This makes the quality of experience (QoE) of the service susceptible to degradation when the Wi-Fi link is underperforming, and it can also inflict QoE unfairness, creating situations where users connected to the same Wi-Fi network feel different levels of QoE. This article presents a system that improves the QoE fairness of DASH video transmission network slicing in the context of Wi-Fi networks. The proposed system slices the wireless resources unevenly among flows, taking into account the characteristics of the video and the QoE demands for each user. Experimental results show that fairness improves by 56% when compared to an unmanaged network, while the mean QoE is reduced by only 5%.     

Cognitive radio architecture evolution: annals of telecommunications

Cognitive radio research has developed dynamic radio spectrum management to enhance spectrum efficiency, e.g., as secondary users in unused TV bands. The location and user context of the mobile wireless user that regulatory bodies and lawmakers view as significant to spectrum interference policies have not been addressed as thoroughly. In addition, quality of service (QoS) provides a starting point but does not guarantee quality of experience (QoE) that depends on quality of information (QoI) which is a function of place, time, and user state in a social setting (e.g., commuting, shopping, or in need of medical assistance). This paper considers the evolution of cognitive radio architecture (CRA) from dynamic spectrum access (DSA) to QoE via an interdisciplinary perspective. Machine perception in visual, acoustic, speech, and text domains can cue the automatic detection of user state in stereotypical situations, enabling cognitive nodes and networks to select from among radio bands and modes more appropriately, thus enabling cognitive wireless networks (CWNs) to deliver higher QoE within technical policy constraints, in a way that makes cost-effective use of embedded and distributed computational intelligence. The control of networks of such cognitive radios requires advances in policy language architectures, so this paper introduces cognitive linguistics for policy languages.     

QoE Model Based Optimization for Streaming Media Service Considering Equipment and Environment Factors

With the development of smart phones, one of the hot research topics for wireless personal communication technologies has begun to transit from reaching higher communication capabilities to better Quality of Experiences (QoE). However, for streaming services, such as online music or online video, which is one of the mainstream services in the future wireless network, there is still no breakthrough optimization beyond the Quality of Service (QoS) hence the optimization results are not satisfactory. Based on our study, this problem could be relieved by altering the criterion of wireless resource allocation from enhancing users?? QoS to enhancing their QoE, which specifically means that the scope of the research is extended from the so-called last mile between the network and the user equipment to the last few inches between the user equipment and the user himself. Unfortunately, it seems that all current QoE researches are still not jointly considering the users?? environment and user equipments?? performance, both of which are paramount factors of the last inches that will influence users?? QoE directly and profoundly. Hence, in this paper, we propose a QoE model involving the environment and equipment factors, and then we use this model to guide the wireless resource allocation. Simulation results show that this resource allocation method will increase the effectiveness of network resource utilization as well as improve the average of satisfaction of users.     

基于用户体验的VLC/WiFi异构网络切换算法

针对可见光通信(VLC)与WiFi组成的异构网络中的网络选择问题,现有工作大多仅关注实际物理网络指标的优化,如信干噪比(SINR)和吞吐量等,而忽视了终端用户的异构需求和服务体验。基于此,该文提出了一种以用户体验质量(QoE)为优化目标的网络切换算法。该算法首先基于平均主观评分(MOS)机制建立离散化的QoE等级模型,然后根据不同网络对应的实际QoE水平给出了相应网络切换准则,当且仅当新网络使得用户QoE等级提升时才进行网络切换,从而在一定程度减小盲目追求容量优化引起的网络切换开销。仿真结果表明,该算法相比现有算法能够在保证QoE水平的前提下显著减小整体的网络切换次数,从而降低网络开销,提升网络性能。      

Non-Intrusive Online Quality of Experience Assessment for Voice Communications

Recently user quality of experience (QoE) is employed in evaluating end user satisfaction in communications systems. Generally, current approaches for QoE assessment are obtrusive, laboratory based and offline. Estimation of user satisfaction in static manner based on mean opinion score is not directly related to instantaneous individual end user contentment. In this paper, based on correlations between user’s physiological signals and her/his feelings about the service quality, a non-intrusive and user centric QoE assessment system for voice communications is developed. The findings of this study indicate that the emotional patterns in response to the changes in channel quality can be adapted to estimate the level of satisfaction in a QoE assessment system in a live manner. Based on experimental results, two categories of users are identified: sensitive and insensitive towards quality degradations. The results indicate that for the sensitive users, our non-intrusive subjective quality assessment method outperforms ITU-T P.563 standard with respect to root mean square error; while, the results are much better among the insensitive users.     

MIMO Scheduling Effectiveness Analysis for Bursty Data Service from View of QoE

In the user selection phrase of the conventional Multiple-input-multiple-output (MIMO) scheduling schemes,the frequent user exchange deteriorates the Quality of user experience (QoE) of the bursty data service.And the channel vector orthogonalization computation results in a high time cost.To address these problems,we propose an inertial scheduling policy to reduce the number of noneffective user exchange,and substitute self-organization policy for channel vector orthogonalization computation to reduce computational complexity.The relationship between the scheduling effectiveness and the inertia of objective function is observed in the simulation.The simulation results show that the inertial scheduling policy effectively reduce the number of potential noneffective scheduling which is inversely proportional to the Mean opinion score (MOS) that quantifies the QoE.Our proposed scheduling scheme provides significant improvement in QoE performance in the simulation.Although the proposed scheduling scheme does not consider the channel vector orthogonalization in the user selection phrase,its throughput approaches the level of the throughput-oriented scheme because of its selforganization scheduling policy.     

Performance of MIMO-UWB for LOS and N-LOS Propagation

Mobile cloud computing (MCC) enables ubiquitous access to a diverse range of Internet multimedia services in a pay-as-you-go economic model. In an MCC environment with highly mobile users, the migration of service requests from one cloud server to another due to user movement may frequently occur. We note that when the load offered to the cloud server is increased beyond the capacity limit, particularly when migrated traffic due to user movement suddenly appears, the probability to disrupt existing services gets higher, consequently resulting in the degradation of user quality of experience (QoE). To keep the service disruption probability at an acceptable level so as to maintain a high user-perceived QoE for different classes of multimedia services, this paper proposes a QoE-aware service continuity strategy for the cloud server in an MCC environment. The strategy is based on the buffer-occupancy threshold policy that differentiates newly arriving service requests coming from the mobile users and offers effective protection for migrated service requests against traffic fluctuation in newly arriving service requests. With the proposed strategy, the cloud server can dynamically change the buffer thresholds for different classes of service requests based on the offered traffic load and the user mobility to improve resource utilization, and, most importantly, to keep the service disruption probability at an acceptable level. Besides, by taking the effect of migrated traffic into account, we develop an analytical model to study the performance of the cloud server using the proposed strategy. With the analytical model, we propose an iterative method to determine the optimal buffer thresholds that maximize resource utilization while keeping an acceptable user QoE for different classes of services.

     

流量业务用户感知的评估方法分析

本文探寻移动数据业务网络参数、性能指标与用户体验之间的关系,分析影响用户感知的因素,提出用现网数据量化用户体验的方法。对于移动数据业务,我们将从移动用户体验,即感知质量QoE的角度出发,分析现网数据业务特征,研究影响业务QoE关键因素,抽象数据业务类型,探索评估各类业务用户感知质量评估的理论依据。     

HTTP自适应流媒体直播系统中的用户体验质量优化

分析HTTP自适应流媒体直播系统中对终端用户体验质量(QoE)产生影响的各类因素及其相互之间的作用关系,对基于服务器端、网络传输以及客户端的QoE优化策略进行总结。认为HTTP自适应流媒体直播系统的QoE优化重点在于降低延时,提出结合网络层和应用层影响因素来降低时延并提升用户QoE的建议。     

Enhancing quality of experience using peer‐to‐peer overlay on device‐to‐device communications

With the recent development of LTE‐A/5G technologies, data sharing among mobile devices offer an attractive opportunity to reduce Internet access. However, it requires smart strategies to share the data with low trade‐offs in time, cost, and energy. Several existing schemes offer a super‐peer‐based two‐tier model using a distributed hash table (DHT) organization for smart devices having device‐to‐device (D2D)/Bluetooth/WiFi capabilities. The primary focus of these schemes has been to reduce Internet usage by increased D2D content sharing. However, the real challenge is not in creating a two‐tier model, but evolving an efficient overlay that offers enhanced opportunities for D2D content sharing over the existing model. In this paper, we formulated a P‐median‐based selection of tier‐1 devices in a distribution network and solved it using the Lagrangian relaxation method. The tier‐2 devices become clients seeking content sharing services from tier‐1 devices. A strong motivation in this work is to raise a user's perception of the grade of service known as quality of experience (QoE). We analyzed the challenge for QoE assessment in resource‐constrained smartphones under the proposed model of enhanced D2D communication. Our focus is to establish a framework to evaluate QoE for applications and services over LTE‐A/5G networks with an improved D2D communication level. The simulation and the experimental results validate the claim that substantial improvements in QoE are possible with the proposed mathematical model for selecting and placing tier‐1 mobile devices and maintaining a DHT for D2D communication.     

Spatial opportunistic transmission for Quality of Experience satisfaction

The capability of Multiple Input Multiple Output (MIMO) to deliver service simultaneously to more than one user is an exceptional characteristic for the cognitive radio (CR) communication. In this paper, statistical optimization techniques are applied to assess the performance of the Quality of Experience (QoE) in CR systems, where each user has different demands. The Multiuser scenario is considered where the transmitter runs the Multibeam Opportunistic Beamforming technique to service more than one user. Closed form expressions are derived for different scenarios and obtained for four QoE indicators in the system. The performance of primary and secondary users in such scenarios are mathematically formulated and the results are compared with computer simulations.     

基于LTE流媒体业务的用户体验质量评估方法研究

针对LTE流媒体业务用户体验质量的评估,本文基于层次分析法的区间估计理论,筛选出了影响用户感知相对重要的关键性能指标KPI,然后从技术因素和非技术因素两个角度分析,建立改进的用户体验质量评估模型。最后采用模糊层次分析法对关键质量指标权重KQI的计算方法进行改进,从而建立了一套完善的评估方法。仿真结果表明,该评估方法兼顾网络客观因素与用户主观感知,能够更好地反映实际的网络质量。     

QoE‐ and energy‐efficient resource optimization in OFDMA networks with bidirectional relaying

Because of the surging demands of multimedia services, quality‐of‐experience (QoE) is becoming an important metric to evaluate network quality from users' perspective. In this paper, resource optimisation to achieve optimal tradeoff between QoE and energy consumption in bidirectional orthogonal frequency‐division multiple‐access relaying networks is addressed so as to provide satisfactory multimedia delivery quality and support green communications. We first formulate a QoE‐energy efficiency tradeoff optimisation where QoE requirements and relaying traffic balance are considered and prove that QoE‐energy efficiency is quasiconcave on QoE, which suggests the existence of a unique global optimal tradeoff point. We then propose an optimisation framework to achieve the optimal tradeoff efficiently. With the framework, we develop resource allocation approaches for two specific relaying strategies, that is, two‐phase decode‐and‐forward relaying with dynamic XOR network coding and compute‐and‐forward relaying with physical network coding via structured codes. Numerical results validate theoretical findings and demonstrate the effectiveness of the proposed optimisation solution for achieving the tradeoff between QoE and energy consumption. Copyright © 2015 John Wiley & Sons, Ltd.     

无线泛在网的用户体验质量综合评估机制(英文)

To assess Quality of Experience (QoE) for multimedia services in wireless ubiquitous networks, integrated QoE assessment mechanism is proposed. Firstly, hierarchical QoE definition considering device capacity and environment factor is introduced, and then corresponding QoE measurement architecture is described. Secondly, quantitative mapping scheme among the defined sets is introduced. Simulation for Video on Demand (VoD) and video telephone service in Universal Mobile Telecommunications System (UMTS) urban...     

基于使用者反馈的用户体验质量管理构架

Recently, Quality of Experience (QoE) has been introduced as a subjective measure of a user’s experience of communication services. QoE was expected to take the place of traditional Quality of Ser-vice (QoS) measure in that QoE may express a direct and accurate user experience. In this paper, we propose a QoE management scheme which is based on a user’s simple feedback. We explain the proposed QoE management steps and the dominant reason extraction algorithm to determine the quality-falling instance. We also present a QoE prediction method that will provide an optimal quality management scheme in communication services. Experiments on mul-timedia streaming service prove the efficiency of the dominant factor extraction algorithm, and the experiment using the QoE prediction method present a very high accuracy. The QoE management scheme proposed in this paper can be generally adapted to any communication services, to increase the efficiency and effectiveness of quality man-agement systems.     

Quality user experience in advanced IP video services

The continuous improvement in the delivery of advanced video services, along with evolved technical conditions at the client side, contributed to the appearance of new methods for the evaluation of quality of service (QoS) and quality of experience (QoE) from the user’s point of view. This article describes the development of a model that correlates QoS parameters and QoE factors with impact on the variation of the user’s perception of the quality. A quality assessment test was performed with 40 participants that ranked more than 140 videos. The detailed analysis of the collected data from the test allowed to conclude that all the considered factors had significant impact on the perceived quality. Those factors were aggregated in a single model using linear regression techniques to join their behavior and associate adequate weights to each factor. The results from validity tests of the model were encouraging, achieving 99 % of accuracy. This model can be considered a new no-reference metric to infer the perceived quality, applicable in many contexts, but essentially as a tool for service providers to estimate the rank customers may give to a content.