Quality of Experience Research Papers (original) (raw)

2025, arXiv (Cornell University)

Multi-Agent Reinforcement Learning (MARL) is nowadays widely used to solve real-world and complex decisions in various domains. While MARL can be categorized into independent and cooperative approaches, we consider the independent approach as a simple, more scalable, and less costly method for large-scale distributed systems, such as network packet forwarding. In this paper, we quantitatively and qualitatively assess the benefits of leveraging such independent agents learning approach, in particular IQL-based algorithm, for packet forwarding in computer networking, using the Named Data Networking (NDN) architecture as a driving example. We put multiple IQL-based forwarding strategies (IDQF) to the test and compare their performances against very basic forwarding schemes and simple topologies/traffic models to highlight major challenges and issues. We discuss the main issues related to the poor performance of IDQF, and quantify the impact of these issues on isolation when training and testing the IDQF models under different model tuning parameters and network topologies/characteristics.

2025

Multi-Agent Reinforcement Learning (MARL) is nowadays widely used to solve real-world and complex decisions in various domains. While MARL can be categorized into independent and cooperative approaches, we consider the independent approach as a simple, more scalable, and less costly method for large-scale distributed systems, such as network packet forwarding. In this paper, we quantitatively and qualitatively assess the benefits of leveraging such independent agents learning approach, in particular IQL-based algorithm, for packet forwarding in computer networking, using the Named Data Networking (NDN) architecture as a driving example. We put multiple IQL-based forwarding strategies (IDQF) to the test and compare their performances against very basic forwarding schemes and simple topologies/traffic models to highlight major challenges and issues. We discuss the main issues related to the poor performance of IDQF and quantify the impact of these issues on isolation when training and...

2025, Deep Science Publishing

2025, Interspeech 2020

The ITU-T Recommendation P.808 provides a crowdsourcing approach for conducting a subjective assessment of speech quality using the Absolute Category Rating (ACR) method. We provide an open-source implementation of the ITU-T Rec. P.808 that runs on the Amazon Mechanical Turk platform. We extended our implementation to include Degradation Category Ratings (DCR) and Comparison Category Ratings (CCR) test methods. We also significantly speed up the test process by integrating the participant qualification step into the main rating task compared to a two-stage qualification and rating solution. We provide program scripts for creating and executing the subjective test, and data cleansing and analyzing the answers to avoid operational errors. To validate the implementation, we compare the Mean Opinion Scores (MOS) collected through our implementation with MOS values from a standard laboratory experiment conducted based on the ITU-T Rec. P.800. We also evaluate the reproducibility of the result of the subjective speech quality assessment through crowdsourcing using our implementation. Finally, we quantify the impact of parts of the system designed to improve the reliability: environmental tests, gold and trapping questions, rating patterns, and a headset usage test.

2025, Interspeech 2015

This paper reports on a crowdsourcing study investigating the influence of trapping questions on the reliability of the collected data. The crowd workers were asked to provide quality ratings for speech samples from a standard database. In addition, they were presented with different types of trapping questions, which were designed based on previous research. The ratings obtained from the crowd workers were compared to ratings collected in a laboratory setting. Best results (i.e. highest correlation with and lowest root-mean-square deviation from the lab ratings) were observed for the type of trapping question, for which a recorded voice was presented in the middle of a random stimuli. The voice explained to the workers that high quality responses are important to us, and asked them to select a specific item to show their concentration. We hypothesize that this kind of trapping question communicates the importance and the value of their work to the crowd workers. Based on Herzberg two-factor theory of job satisfaction, the presence of factors, such as acknowledgment and the feeling of being valued, facilitates satisfaction and motivation, and eventually leads to better performance.

2025, 2021 13th International Conference on Quality of Multimedia Experience (QoMEX)

Traditionally, Quality of Experience (QoE) for a communication system is evaluated through a subjective test. The most common test method for speech QoE is the Absolute Category Rating (ACR), in which participants listen to a set of stimuli, processed by the underlying test conditions, and rate their perceived quality for each stimulus on a specific scale. The Comparison Category Rating (CCR) is another standard approach in which participants listen to both reference and processed stimuli and rate their quality compared to the other one. The CCR method is particularly suitable for systems that improve the quality of input speech. This paper evaluates an adaptation of the CCR test procedure for assessing speech quality in the crowdsourcing set-up. The CCR method was introduced in the ITU-T Rec. P.800 for laboratory-based experiments. We adapted the test for the crowdsourcing approach following the guidelines from ITU-T Rec. P.800 and P.808. We show that the results of the CCR procedure via crowdsourcing are highly reproducible. We also compared the CCR test results with widely used ACR test procedures obtained in the laboratory and crowdsourcing. Our results show that the CCR procedure in crowdsourcing is a reliable and valid test method.

2025, Quality and User Experience

Subjective speech quality assessment has traditionally been carried out in laboratory environments under controlled conditions. With the advent of crowdsourcing platforms tasks, which need human intelligence, can be resolved by crowd workers over the Internet. Crowdsourcing also offers a new paradigm for speech quality assessment, promising higher ecological validity of the quality judgments at the expense of potentially lower reliability. This paper compares laboratory-based and crowdsourcing-based speech quality assessments in terms of comparability of results and efficiency. For this purpose, three pairs of listening-only tests have been carried out using three different crowdsourcing platforms and following the ITU-T Recommendation P.808. In each test, listeners judge the overall quality of the speech sample following the Absolute Category Rating procedure. We compare the results of the crowdsourcing approach with the results of standard laboratory tests performed according to t...

2025, Lecture Notes in Computer Science

The question of our study is how to provision a diffserv (differentiated service) intra-net serving three classes of traffic, i.e., voice, real-time data (e.g. stock quotes), and best-effort data. Each class of traffic requires a different level of QoS (Quality of Service) guarantee. For VoIP the primary QoS requirements are delay and loss; for realtime data response-time. Given a network configuration and anticipated workload of a business intra-net, we use ns-2 simulations to determine the minimum capacity requirements that dominate total cost of the intranet. To ensure that it is worthwhile converging different traffic classes or deploying diffserv, we cautiously examine capacity requirements in three sets of experiments: three traffic classes in i) three dedicated networks, ii) one network without diffserv support , and iii) one network with diffserv support. We find that for the business intra-net of our study, integration without diffserv may need considerable over-provisioning depending on the fraction of real-time data in the network. In addition, we observe significant capacity savings in the diffserv case; thus conclude that deploying diffserv is advantageous. The relations we find give rise to, as far as we know, the first rule of thumb on provisioning a diffserv network for increasing real-time data.

2025, 2017 IEEE 85th Vehicular Technology Conference (VTC Spring)

2025, 2017 IEEE 18th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM)

This paper introduces research that addresses the subjective assessment of Quality of Experience (QoE) during the entire life cycle of a video session. We define a video session life cycle as the time from when a user attempts to initiate playback, until such time that the video ends either from normal video conclusion or through a network-induced failure. We provide a detailed description of our assessment methodology designed to discern whether a user's QoE would be impacted by the presence of failures. To accomplish this, we carefully select various test conditions to take into consideration the rating scale used, the types of impairments and failures seen by the user, and whether impaired videos are seen together with failed videos in multi-video sessions. The selection and creation of source video sequences are also discussed, as well as the use of between-subjects and within-subjects approaches for running our experiments in a controlled laboratory setting. Statistical analysis was carried out to interpret our experimental results. We compared the results of the between-subjects measures and the results of the within-subjects measures, and concluded that the introduction of a scale with an extended lower bound enabled subjects to more clearly express their dissatisfaction of videos with failures when compared to the traditional ITU 5-point rating scale. In addition, we observed that videos that were simply impaired but concluded normally did not have a statistically significant difference when an extended scale was used.

2025, Proceedings of the Human Factors and Ergonomics Society Annual Meeting

In this paper we explore how memories of experience with streaming video affect Quality of Experience (QoE) indicators that are of interest to service providers and marketers. Since observations of experience are time consuming, and the effects of technical quality (TQ) are difficult to entangle from content quality (CQ), we examined the impact of a visualization methodology for assessing experiences. A study was carried out to examine how well overall technical quality (TQ) judgments for a sequence of visualized video experience (a picture of a red video playbar with yellow portions indicating disrupted video in place of actually viewed video) would correspond to overall TQ judgments made after watching a sequence of actual videos. Sequencing effects found in overall TQ ratings, made after viewing visualizations (with their overlaid disruptions) were similar to sequencing effects found after viewing actual videos. However, the sequencing effects after viewing the visualizations wer...

2025, 2016 IEEE International Conference on Communications (ICC)

In this paper, we study the relationships between Quality of Service (QoS) and Quality of Experience (QoE) in a session-based Over-The-Top (OTT) video service. A number of Performance Metrics (PMs) with and without the existence of failures during a video are examined. As QoE factors, Technical Quality (TQ) and Acceptability are used. We analyze the correlation between QoS performance metrics and QoE factors, and find new PMs should be employed because failures are included in QoE evaluation. We also summarize the relationships between QoS metrics and QoE factors through machine learning approaches. Using decision tree, we have a general idea about the relationships between PMs and QoE factors. We also understand the impact caused by failures and the value of rating scales.

2025, Electronics

This research focuses on intelligent unmanned aerial vehicle (UAV)-based, real-time video surveillance to ensure better monitoring and security of remote locations over 4G-LTE cellular networks by maximizing end-user quality of experience (QoE). We propose a novel server-based crosslayer rate-adaptive scheme (SCRAS) for real-time video surveillance over 4G-LTE networks using UAVs. Our key contributions are: (1) In SCRAS, mobile UAVs having preprogrammed flight co-ordinates act as servers, streaming real-time video towards a remote client; (2) server-side video rate adaptation occurs in 4G-LTE based on the physical characteristics of the received signal conditions due to variations in the wireless channel and handovers; (3) SCRAS is fully automated and independent of client assistance for rate adaptation, as it is intended for real-time, mission-critical surveillance applications; (4) SCRAS ensures that during rate adaptation, the current video frame should not be damaged by completi...

2025

In large scale IP Television (IPTV) and Mobile TV distributions, the video signal is typically encoded and transmitted using several quality streams, over IP Multicast channels, to several groups of receivers, which are classified in terms of their reception rate. As the number of video streams is usually constrained by both the number of TV channels and the maximum capacity of the content distribution network, it is necessary to find the selection of video stream transmission rates that maximizes the overall user satisfaction. In order to efficiently solve this problem, this paper proposes the Dynamic Programming Multi-rate Optimization (DPMO) algorithm. The latter was comparatively evaluated considering several user distributions, featuring different access rate patterns. The experimental results reveal that DPMO is significantly more efficient than exhaustive search, while presenting slightly higher execution times than the non-optimal Multi-rate Step Search (MSS) algorithm.

2025, Sensors

Nowadays, it is quite a challenge for app owners to keep users engaged with an app. Currently, the level of user abandonment is one of the key parameters that application owners are interested in. To meet these challenges, we conduct an extended study of a previously proposed solution that significantly reduces the abandonment rate of a given application. The investigated solution is based on the methods of fairness using the QoE and QoS approach. This paper shows that application abandonment ratios can be reduced by using an appropriate approach to fair bandwidth allocation. Adjusting the bandwidth allocation to users, taking into account the quality of the user experience, has a more effective effect on reducing app abandonment ratios than if quality of service is taken into account. This is because the users make the decision to abandon the application based on their feelings rather than technical parameters. In order to effectively reduce application abandonment ratios, a suitab...

2025

The stringent requirements of wireless multimediatransmission lead to very high radio spectrum solicitation. Although the radio spectrum is considered as a scarce resource, theissue with spectrum availability is not scarcity, but the inefficientutilization. Unique characteristics of cognitive radio (CR) suchas flexibility, adaptability, and interoperability, particularly havecontributed to it being the optimum technological candidate toalleviate the issue of spectrum scarcity for multimedia communications. However, multimedia communications over CRnetworks (MCRNs) as a bandwidth-hungry, delay-sensitive, andloss-tolerant service, exposes several severe challenges speciallyto guarantee quality of service (QoS) and quality of experience(QoE). As a result, to date, different schemes based on source andchannel coding, multicast, and distributed streaming, have beenexamined to improve the QoS/QoE in MCRNs. In this paper,we survey QoS/QoE provisioning schemes in MCRNs. We firstdiscuss the ...

2025

This study explores the relationship between individual customer service items and satisfaction with facilities, services, information, recreation experience and overall quality of fishing for a diverse group of anglers at lakes in the New England region. Recent attention to customers and their experiences and attitudes has increased the interest of, both managers and researchers in issues like customer satisfaction. In an attempt to make satisfaction models more useful, Burns et al. (1999) created a customer satisfaction model with four domains (facilities, services, information, and recreation experience). This model was designed to be more easily understood by recreation researchers and managers because the items within the domains were more relevant and tangible. The domains used were also believed to be flexible in nature and adaptable to the needs of the specific recreation area under study. This study builds on previous research by continuing exploration of the factors influencing satisfaction with the recreation experience. The relationships between twelve customer service items and satisfaction with the four domains of facilities, services, information and the recreation experience were tested. The individual items were most strongly related to satisfaction within the facilities domain. Results also revealed direct relationships between these variables and overall satisfaction with the fishing experience. Satisfaction with the number of fish a person can catch and the services domain showed the most influence on overall satisfaction with the fishine ex~erience.

2025

The use of 3D stereoscopic technology with high quality videos can provide visual entertainment to viewers. However, the bandwidth of typical communication channels cannot transmit uncompressed 3D videos, resulting in the need for video quality compression. This paper presents a series of preliminary studies to investigate the subjective perception of uncompressed and compressed video sequences, and proposes the ‘hybrid’ sequencing of uncompressed and compressed content in a single stereoscopic 3D video as an alternative approach for limited bandwidth transmission. However, the hybrid uncompressed/compressed sequencing of stereoscopic 3D video may affect the correlation between the left and right views of the stereoscopic videos required for depth perception, potentially leading to lower Quality of Experience (QoE) of viewers. This paper therefore investigates both the objective and subjective quality evaluation of the proposed hybrid sequencing of stereoscopic video sequences. Init...

2025, Journal of Engineering, Electrical and Informatics

The purpose of this research is to explore the application of artificial intelligence (AI) techniques, particularly Machine Learning, in predicting quality of service (QoS) on mobile networks, with the main focus being to test the ability of AI models to predict several QoS parameters, involving several important stages that reflect best practices in the development of artificial intelligence (AI)based predictive systems for mobile networks. The dataset used in this study consists of data collected from simulations of mobile networks with various load and latency conditions. The parameters measured include Throughput, Latency and Packet Loss. Model evaluation was carried out to measure prediction performance using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE) measurements. The AI models used include machine learning algorithms consisting of K-Nearest Neighbors (KNN) for classification and regression on QoS datasets, Support Vector Machine (SVM) to model non-linear relationships between QoS parameters and input variables, and Deep Learning (LSTM=Long Short-Term Memory) used to predict QoS based on time sequence data. This study found that LSTM-based deep learning models have the lowest prediction error rate in estimating packet loss, so they can provide the most accurate results in predicting QoS on mobile networks. This approach is capable of handling data that is sequential and has significant time dependence, making it more suitable for dynamic mobile network applications.

2025

Recommended precautions because of Covid-19 for perceptual, behavioural, quality and user experience experiments with test persons in indoor labs Based on the recommendations from the Public Health Agency of Sweden (Folkhälsomyndigheten; FHM) and a set of internal rules from RISE, the following rules are published for how to conduct experiments involving test persons in the times of the pandemic Covid-19. The recommendations are for non-invasive and non-medical tests, e.g. perceptual, consumer, ergonomic and human-computer interaction tests taking place in an indoor laboratory. Specifically, in this document we are specifying how experiments with test persons targeting audio and visual presentations should be done considering necessary precautions imposed by the Covid-19 pandemic. Laboratory experiments with test persons, as it involves inviting people to the lab, require particular planning and careful consideration, if they are to be carried out safely because of the risks imposed by the Covid-19 pandemic. The safety aspects are valid for both the invited test persons and are equally important for the health of the test leaders.

2025, arXiv (Cornell University)

Over the last decade, the bandwidth expansion and MU-MIMO spectral eciency have promised to increase data throughput by allowing concurrent communication between one Access Point and multiple users. However, we are still a long way from enjoying such MU-MIMO MAC protocol improvements for bandwidth hungry applications such as video streaming in practical WiFi network settings due to heterogeneous channel conditions and devices, unreliable transmissions, and lack of useful feedback exchange among the lower and upper layers' requirements. This paper introduces MuViS, a novel dual-phase optimization framework that proposes a Quality of Experience (QoE) aware MU-MIMO optimization for multi-user video streaming over IEEE 802.11ac. MuViS rst employs reinforcement learning to optimize the MU-MIMO user group and mode selection for users based on their PHY/MAC layer characteristics. The video bitrate is then optimized based on the user's mode (Multi-User (MU) or Single-User (SU)). We present our design and its evaluation on smartphones and laptops using 802.11ac WiFi. Our experimental results in various indoor environments and congurations show a scalable framework that can support a large number of users with streaming at high video rates and satisfying QoE requirements.

2025

As online services become more pervasive and complex, customer experience is becoming a key competitive differentiator. Customer expectations are rising, and bandwidth requirements of online services are increasing. Internet service providers are faced with a difficult tradeoff between managing the costs of services and bandwidth requirements on the one hand, and meeting customer expectations on the other. At present there is little to guide service providers in managing the human side of this tradeoff. While there is considerable interest in quality of experience from an engineering perspective, there is a need to supplement that work with research based on a human factors approach. The goal of the research reported here is to determine how a series of satisfying experiences and frustrating events lead to longer term attitudes of satisfaction or dissatisfaction over time and, ultimately, to loyalty towards a service provider or Likelihood to Recommend (L2R). The ultimate objective of the research will be to develop models that can predict overall satisfaction, and likelihood to churn, based on network probe data (data relating to online service impairments and failures experienced by a customer), service context and customer profile. These models can then be used to optimize services design and delivery, leading to more satisfied consumers and more profitable companies. In this report we introduce the initial outlines of a model of likelihood to recommend for online services. The ultimate goal is to develop a detailed model based on data that is either available from marketing sources or that can be collected automatically from network probes.

2025

This paper presents a subscription-based overlay network that supports efficient file parallel downloading. First, the system lets users register to a central server and allows the server to incrementally build a topology graph cont aining the network connections among the subscribers. With thi s topology graph in place, we address the challenges of minimi zing network traffic and choosing the set of nodes from which a chosen file is downloaded through several concurrent connections. Active subscribers and other users are organized in an arb itrary peerto-peer network. When a subscriber wants downloadin g a chosen file, it submits a search query to the overlay network and obtains a list of nodes having this file. Then, this list is submitted to the server, which ranks the nodes considering both thei r network distance to the client and their workloads. Second, based on these top nodes, a bandwidth-aware parallel downloading t echnique is executed. If a top node becomes offline, eith...

2025

In this paper, we introduce a joint flow control and scheduling algorithm for multi-hop cognitive radio networks with spectrum underlay. Our proposed algorithm maximizes the total utility of secondary users while stabilizing the cognitive radio network and still satisfies the total interference from secondary users to primary network is less than an accepted level. Based on Lyapunov optimization technique, we show that our scheme is arbitrarily close to the optimal.

2025, Zenodo (CERN European Organization for Nuclear Research)

User-centric service and application management focuses on the Quality of Experience (QoE) as perceived by the end user. Thereby, the goal is to maximize QoE while ensuring fairness among users, e.g., for resource allocation and scheduling in shared systems. Although the literature suggests to consider consequently QoE fairness, there is currently no accepted definition of QoE fairness. The contribution of this paper is the definition of a generic QoE fairness index F which has desirable key properties as well as the rationale behind it. By using examples and a measurement study involving multiple users downloading web content over a bottleneck link, we differentiate the proposed index from QoS fairness and the widely used Jain's fairness index. Based on results, we argue that neither QoS fairness nor Jain's fairness index meet all of the desirable QoE-relevant properties which are met by F . Consequently, the proposed index F may be used to compare QoE fairness across systems and applications, thus serving as a benchmark for QoE management mechanisms and system optimization.

2025, Proceedings of the 10th ACM Multimedia Systems Conference

Streaming videos over cellular networks is highly challenging. Since cellular data is a relatively scarce resource, many video and network providers offer options for users to exercise control over the amount of data consumed by video streaming. Our study shows that existing data saving practices for Adaptive Bitrate (ABR) videos are suboptimal: they often lead to highly variable video quality and do not make the most effective use of the network bandwidth. We identify underlying causes for this and propose two novel approaches to achieve better tradeoffs between video quality and data usage. The first approach is Chunk-Based Filtering (CBF), which can be retrofitted to any existing ABR scheme. The second approach is QUality-Aware Data-efficient streaming (QUAD), a holistic rate adaptation algorithm that is designed ground up. We implement and integrate our solutions into two video player platforms (dash.js and ExoPlayer), and conduct thorough evaluations over emulated/commercial cellular networks using real videos. Our evaluations demonstrate that compared to the state of the art, the two proposed schemes achieve consistent video quality that is much closer to the user-specified target, lead to far more efficient data usage, and incur lower stalls.

2025

This paper presents selected issues related to Internet Access Service (IAS) quality assessment. Nowadays, it is not only the price, but quality, that influences the decisions of users regarding the choice of Internet Service Provider (ISP). According to European documents, users have a right to be informed of IT services offered by different providers. However, there is a problem: what, where and how to measure the service quality? The second issue is: how service quality is perceived by users and, finally, how to correlate these two different points of view. We discuss selected objective measures of the Internet Access Service and present measurement scenarios. The users' point of view and the subjective measure of quality is also presented. In the second part of the paper, we show how the users perceive Internet Access by the services they use. An example of building the Quality of Experience model for the WWW service is also presented.

2025, IJARST

Mobile network management and drive tests provide services that give a clear insight into the quality of mobile network coverage and other wireless networks including identifying areas of poor signal quality and identification of black spots. This research investigates the potential of supervised machine learning models to predict mobile network performance, focusing on Coventry University and Coventry City Center, United Kingdom. The measured download speed represented as Downlink bit rate (DL_bit rate) at these locations are used to obtain user performance data using Lebera mobile virtual network operator SIM card in order to assist with the visualization of the mobile network performance maps. The study explores the application of various machine learning models, including Random Forest, Linear Regression, Gradient Boosting, Support Vector Regression (SVR), and K-Nearest Neighbors (KNN), to forecast mobile network throughput speed (DL_Throughput). Among the models, the Random Forest Regression (RFR) model demonstrated the highest accuracy, with a Mean Absolute Error (MAE) of 6.79 and an R-squared (R²) value of 0.496, indicating its effectiveness in capturing network performance variability. The findings highlight the considerable promise of machine learning in optimizing mobile networks, enabling telecommunications providers to automate network management, enhance resource allocation, and improve the Quality of user Experience (QoE). The application of predictive analytics in this context offers significant advantages, including increased network efficiency, enhanced user satisfaction, and reduced operational costs. This study underscores the importance of integrating AI-driven predictive models into mobile network optimization strategies to meet the evolving demands of urban environments.

2025

Superior network Quality of Experience (QoE) is important for Mobile Network Operators (MNO) as it ensures they increase profit margins, attract new customers and differentiate themselves from the competition by providing better quality guarantees. In this paper, we propose a QoE hexagram model that comprises six Key Quality Indicators (KQI). In this model, we introduced an additional KQI, Terminal Quality. Other new metrics like Packet Corruption Rate and Service Access Time were also incorporated. Furthermore, several experiments were conducted by introducing disturbances using the NetEm tool. The QoE value obtained from our model is an indication of the overall acceptability of the applications and services as perceived subjectively by the end users.

2025, International Journal of Adaptive, Resilient and Autonomic Systems

Accessing multimedia services via fixed and wireless networks has become common practice. These services are typically much more sensitive to packet loss, delay and/or congestion than traditional services. In particular, multimedia data is often time critical and, as a result, network issues are not well tolerated and significantly deteriorate the user’s Quality of Experience (QoE). Therefore, the authors propose a QoE optimization platform that is able to mitigate problems that might occur at any location in the delivery path from service provider to customer. More specifically, the distributed architecture supports overlay routing to circumvent erratic parts of the network core. In addition, it comprises proxy components that realize last mile optimization through automatic bandwidth management and the application of processing on multimedia flows. This paper introduces a trans-coding service for this proxy component which enables the transformation of H.264/AVC video flows to an ...

2025

This work addresses the issues concerned with the provision of scalable video services over heterogeneous networks particularly with regards to dynamic adaptation and user’s acceptable quality of service. In order to provide and sustain an adaptive and network friendly multimedia communication service, a suite of techniques that achieved automatic scalability and adaptation are developed. These techniques are evaluated objectively and subjectively to assess the Quality of Service (QoS) provided to diverse users with variable constraints and dynamic resources. The research ensured the consideration of various levels of user acceptable QoS The techniques are further evaluated with view to establish their performance against state of the art scalable and non-scalable techniques. To further improve the adaptability of the designed techniques, several experiments and real time simulations are conducted with the aim of determining the optimum performance with various coding parameters and...

2025, IEEE Access

Network resource management is one of the key technologies needed to ensure that multiple applications in edge networks provide reliable and stable performance. Although throughput has previously been seen as the primary network performance metric, recent applications do not focus on throughput alone. Instead, Quality of Experience (QoE) is attracting significant attention as an indicator of network resource management performance because it allows a wide variety of applications to be compared within a single metric. In this study, we tackle QoE measurements for a video streaming service as a way to evaluate QoE-based network management. However, there are several problems related to measuring QoE. For example, in-network components are difficult to measure because QoE is normally measured at end-points, and several properties that are deeply related to application settings are required for those calculations. Additionally, the measurements set forth in the International Telecommunication Union's ITU-T G.1071 standard require a certain duration, which is too long for network resource management evaluations. Therefore, this paper proposes a two-staged in-network QoE estimation method for video flows that can resolve these issues. In the first stage, we focus on producing a fast and rough QoE estimate to start forwarding the arriving flow onto an appropriate route as soon as possible. Next, the second stage is designed to produce precise QoE estimations based on careful long-duration measurements. In both stages, the proposed method uses a parameter estimation process that converts in-network information to end-point information for QoE calculations by following ITU-T G. 1071 and corrects measurement errors reducing QoE calculation errors to the greatest extent possible. Through experimental evaluations, we then demonstrate that the QoEs of all flows can be maximized by selecting appropriate routes based on the predicted QoE at the first stage, and that the accuracy of the QoE estimation at the second stage can be improved in real-time even when packet losses occur.

2025, 2008 IEEE International Conference on Multimedia and Expo

In this paper, we derive an analytical model for the evaluation of the performance of a Video on Demand (VoD) system. The model estimates the mean waiting time achievable by the Popularity-Aware Partial cAching (PAPA) algorithm from our previous work. Two approximation strategies are proposed for low computational complexity. Furthermore, we also consider the influence of a starting point shift on the quality of experience and combine the two factors into a universal user satisfaction metric. In order to find the relation between the two impairments, waiting time and starting point shift, sophisticated subjective tests are performed. With the final score model, a more comprehensive evaluation of the system can be obtained with very low computational complexity.

2025

The Video on Demand (VoD) service is becoming a dominant service in the telecommunication market due to the great convenience regarding the choice of content items and their independent viewing time. However, it comes with the downsides of high server storage and capacity demands because of the large variety of content items and the high amount of traffic generated for serving each request. Storing part of the popular contents on the peers brings certain advantages but, it still has issues regarding the overall traffic in the core of the network and the scalability. Therefore We propose a P2P assisted model for streaming VoD contents that takes advantage of the clients unused uplink and storage capacity to serve requests of other clients and present popularity based schemes for distribution of both the popular and unpopular contents on the peers with the objective to reduce the streaming traffic in the core of the network, improve the responsiveness of the system and increase its scalability.

2025, 2012 Fourth International Workshop on Quality of Multimedia Experience

Transmission errors are the main cause of degradation of the quality of real broadcasted video services. Therefore, knowing their impact on the quality of experience of the end users is a crucial issue. For instance, it would help to improve the performance of the distribution systems, and to develop monitoring tools to automatically estimate the quality perceived by the viewers. In this paper we validate a subjective evaluation approach specifically designed to obtain meaningful results of the effects of degradations caused by transmission errors. This methodology has been already used in our previous works with monoscopic and stereoscopic videos. The validation is done by comparing the subjective ratings obtained for typical transmission impairments with the proposed methodology and with the standard method Absolute Category Rating. The results show that the proposed approach could provide more representative evaluations of the quality of experience perceived by end users of conventional and 3D broadcasted video services.

2025

Purpose: This study explores how the dimensions of creativity—specifically person, process,
product, and press—affect tourists’ behavioural intentions. Additionally, this study examines
how experience quality mediates these relationships.
Methodology/Design/Approach: This study used a survey instrument to gather data from 500
creative tourists in Malaysia. To test the structural model, Partial Least Squares Structural
Equation Modelling (PLS-SEM) was employed.
Findings: The result highlights the influence of the four Ps of creativity on the behavioural
intentions of tourists within the creative tourism sector. The study also investigates how
experience quality affects these relationships
Originality of the research: The novelty of this study lies in the integration of the four Ps of
creativity and experience quality into a single model for predicting the future behaviour of
creative tourists.
Keywords creativity, experience quality, behavioural intentions

2025, 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)

Voice services has been for a very long time the primary source of income for mobile network operators. Even with the increasing importance of the data traffic, voice services will keep playing a key role and will not disappear with the transition to a networking model based on the IP protocol. Moreover, the key industry players diagnosed years ago that mobile subscribers wouldn't accept a significant degradation in the quality of their voice services. Because of that, it becomes critical to ensure the Quality of Experience (QoE) in the transition to new generation networks based on packet switching communications. The work in the present thesis has aimed to analyze the behavior and the dependencies in the different voice services over IP (VoIP), as well as to identify optimal configurations, potential enhancements and methodologies to ensure acceptable quality levels while minimizing the costs.

2025

(For an explanation of the roles of each group see the preface in Section 0.

2025, 2008 IEEE International Conference on Multimedia and Expo

2025, arXiv (Cornell University)

Middleboxes such as web proxies, firewalls, etc. are widely deployed in today's network infrastructure. As a result, most protocols need to adapt their behavior to co-exist. One of the most commonly used transport protocols, QUIC, adapts to such middleboxes by falling back to TCP, where they block it. In this paper, we argue that the blind fallback behavior of QUIC, i.e., not distinguishing between failures caused by middleboxes and that caused by network congestion, hugely impacts the performance of QUIC. For this, we focus on YouTube video streaming and conduct a measurement study by utilizing production endpoints of YouTube by enabling TCP and QUIC at a time. In total, we collect over 2600 streaming hours of data over various bandwidth patterns, from 5 different geographical locations and various video genres. To our surprise, we observe that the legacy setup (TCP) either outperforms or performs the same as the QUIC-enabled browser for more than 60% of cases. We see that our observation is consistent across individual QoE parameters, bandwidth patterns, locations, and videos. Next, we conduct a deep-dive analysis to discover the root cause behind such behavior. We find a good correlation (0.3 -0.7) between fallback and QoE drop events, i.e., quality drop and re-buffering or stalling. We further perform Granger causal analysis and find that fallback Granger causes either quality drop or stalling for 70% of the QUIC-enabled sessions. We believe our study will help designers revisit the decision to enable fallback in QUIC and distinguish between the packet drops caused by middleboxes and network congestion.

2025

The television industry has undergone a massive transformation with the rise of Internet Protocol Television (IPTV). Unlike traditional cable and satellite TV, IPTV leverages the internet to deliver content, offering flexibility, interactivity, and enhanced viewing experiences. This paper explores the working mechanism of IPTV, its technological foundations, and its potential future in the rapidly evolving digital landscape

2025

Certain commercial equipment and materials are identified in this report to specify adequately the technical aspects of the reported results. In no case does such identification imply recommendation or endorsement by the National Telecommunications and Information Administration, nor does it imply that the material or equipment identified is the best available for this purpose.

2025

We present the design, preparation, and analysis of a subjective experiment on typical HDTV sequences and scenarios. This experiment follows the guidelines of ITU and VQEG in order to obtain reproducible results. The careful selection of content and distortions extend over a wide and realistic range of typical transmission scenarios. Detailed statistical analysis provides important insight into the relationship between technical parameters of encoding, transmission and decoding and subjectively perceived video quality.

2025, PloS One

This research explores the apology strategies employed by international tourists visiting Saudi Arabia, particularly in the context of the Kingdom's rapid tourism expansion under Vision 2030. With the introduction of new tourism policies, the country has opened itself to a wide range of international visitors, increasing the likelihood of cultural missteps. The study investigates how tourists navigate Saudi Arabia's conservative social norms, focusing on factors such as language use, cultural awareness, and the perceived severity of offenses. Data were collected through qualitative focus group interviews with international tourists, analyzing how apology strategies are influenced by social dynamics, gender norms, and power structures. The findings suggest that tourists who demonstrate cultural sensitivity, particularly by using Arabic, are more likely to have their apologies accepted. The study highlights the importance of cross-cultural competence in managing tourist-local interactions and provides insights for tourism operators and policymakers on improving the tourist experience in Saudi Arabia. The research contributes to a deeper understanding of cross-cultural communication in the context of a rapidly growing tourism industry.

2025, IEEE Transactions on Broadcasting

Integrating joint network function virtualization (NFV) and software-defined networks (SDNs) with digital televisions (TVs) into home environments, has the potential to provide smart TV services to users, and improve their quality of experience (QoE). In this regard, this paper focuses on one of the next generation services so-called follow me service (FMS). FMS is a service offered by 5gNB to user equipments (UEs) in indoor environments (e.g., home), it enables its clients to use their smart phones to select media content from content servers, then cast it on the nearest TV set (e.g., living room) and continue watching on the next TV set (e.g., kitchen) while moving around the indoor coverage area. FMS can be provisioned by utilizing UEs geolocation information and robust mechanisms for switching between multiple 5G radio access technologies (RATs), based on the intelligence of the SDN/NFV intelligent home IP gateway of the Internet of Radio Light (IoRL) project paradigm. In view that the actual IoRL system is at its early development stage, we step forward by using Mininet platform to integrate SDN/NFV virtualization into 5G multi-RAT scenario and provide performance monitoring with measurements for the identified service. Simulation results show the effectiveness of our proposal under various use case scenarios by means of minimizing the packet loss rate and improving QoE of the home users.

2025, Transactions on Emerging Telecommunications Technologies

Today, maintaining the best quality of experience (QoE) as the subjective perception of end-users is one of the most important requirements of both wireless and wired networks. To achieve this goal, we frequently use network functions such as admission control, resource management, routing and traffic control. We focus on the design and evaluation of a QoEaware routing mechanism. We present an end-to-end model where Smartphone users connect to content servers through a wired network across a wireless access network. We propose an adaptive and evolutionary system with a QoE-aware routing protocol, namely QoE Q-learning-based adaptive routing. Our experimental results demonstrate significant performance improvements in mean opinion score for various network loads, convergence time during the initialisation phase and control overheads over other traditional approaches.

2025, Lecture Notes in Computer Science

Recently, wealthy network services such as Internet protocol television (IPTV) and Voice over IP (VoIP) are expected to become more pervasive over the Next Generation Network (NGN). In order to serve this purpose, the quality of these services should be evaluated subjectively by users. This is referred to as the quality of experience (QoE). The most important tendency of actual network services is maintaining the best QoE with network functions such as admission control, resource management, routing, traffic control, etc. Among of them, we focus here on routing mechanism. We propose in this paper a protocol integrating QoE measurement in routing paradigm to construct an adaptive and evolutionary system. Our approach is based on Reinforcement Learning concept. More concretely, we have used a least squares reinforcement learning technique called Least Squares Policy Iteration. Experimental results showed a significant performance gain over traditional routing protocols.

2025, Lecture Notes in Computer Science

Actually, wealthy network services such as Internet protocol television (IPTV) and Voice over IP (VoIP) are expected to become more pervasive over the Next Generation Network (NGN). In order to serve this purpose, the quality of these services should be evaluated subjectively by users. This is referred to as the quality of experience (QoE). However, there are many issues that may impact user's perception in many different ways. This paper surveys the QoE models and systems for existing and future network services.