Visual User Experience Difference: Image compression impacts on the quality of experience in augmented binocular vision

2016 ◽  
Author(s):  
Patrick Seeling
Keyword(s):  
Image Compression ◽  
User Experience ◽  
Binocular Vision ◽  
Quality Of Experience ◽  
Difference Image

Improving Quality of Experience of Subscribers through Post Deployment Network Planning in UMTS Cellular Networks

2012 ◽  
Vol 8 (3) ◽  
pp. 1-27
Author(s):  
Samir Kumar Sadhukhan ◽  
Swarup Mandal
Keyword(s):  
User Experience ◽  
Cellular Network ◽  
Quality Of Experience ◽  
Service Management ◽  
Cost Effective ◽  
Management Problem ◽  
Network Service ◽  
Heuristic Techniques ◽  
Effective Manner

It is an established fact that cost of churning is a common concern for being profitable in the cellular network service provider’s space. Service providers can view this problem as a service management problem and can have a solution to enhance the stickiness of subscribers by managing the quality of user experience. Quality of Experience (QoE) is important in contrast to Quality of Service (QoS). Three basic components of service management are stage, prop, and user experience. In this cellular network service context, network infrastructure acts as prop. Prop needs to be flexible to enable the personalization in providing the service. In reality the major challenge for a service provider is keep the fitment between prop and the dynamic changes in subscriber profile in a cost effective manner. To define the problem more precisely, the authors take the conventional UMTS cellular network. Here, operators have considered single-homing of RNCs to MSCs/SGSNs (i.e., many-to-one mapping) with an objective to generate service at lower cost over a fixed period of time. However, a single-homing network does not remain cost-effective and flexible anymore when subscribers later begin to show specific inter-MSC/SGSN mobility patterns over time. This necessitates post-deployment topological extension of the network in which some specific RNCs are connected to two MSCs/SGSNs via direct links resulting in a more complex many-to-two mapping structure in parts of the network. The authors formulate the scenario as a combinatorial optimization problem and solve the NP-Complete problem using three meta-heuristic techniques, namely Simulated Annealing (SA), Tabu search (TS), and Ant colony optimization (ACO). They then compare these techniques with a novel optimal heuristic search method that the authors propose typically to solve the problem. The comparative results reveal that the search-based method is more efficient than meta-heuristic techniques in finding optimal solutions quickly.

scholarly journals FRAMEWORK FOR MODELLING MOBILE NETWORK QUALITY OF EXPERIENCE THROUGH BIG DATA ANALYTICS APPROACH

2017 ◽  
Author(s):  
Ayisat Wuraola Yusuf-Asaju ◽  
Zulkhairi Md. Dahalin ◽  
Azman Ta’a
Keyword(s):  
User Experience ◽  
Data Analytics ◽  
Network Performance ◽  
Laboratory Experiments ◽  
Quality Of Experience ◽  
Big Data Analytics ◽  
Mobile Network ◽  
Mobile Internet ◽  
Mobile Network Operators

The increase in the usage of different mobile internet applications can cause deterioration in the mobile network performance. Such deterioration often declines the performance of the mobile network services that can influence the mobile Internet user’s experience, which can make the internet users switch between different mobile network operators to get good user experience. In this case, the success of mobile network operators primarily depends on the ability to ensure good quality of experience (QoE), which is a measure of users’ perceived quality of mobile Internet service. Traditionally, QoE is usually examined in laboratory experiments to enable a fixed contextual factor among the participants even though the results derived from these laboratory experiments presented an estimated mean opinion score representing perceived QoE. The use of user experience dataset involving time and location gathered from the mobile network traffic for modelling perceived QoE is still limited in the literature. The mobile Internet user experience dataset involving the time and location constituted in the mobile network can be used by the mobile network operators to make data-driven decisions to deal with disruptions observed in the network performance and provide an optimal solution based on the insights derived from the user experience data. Therefore, this paper proposed a framework for modelling mobile network QoE using the big data analytics approach. The proposed framework describes the process of estimating or predicting perceived QoE based on the datasets obtained or gathered from the mobile network to enable the mobile network operators effectively to manage the network performance and provide the users a satisfactory mobile Internet QoE.  

PhD thesis: Quality of experience characterization and provisioning in mobile cellular networks

2019 ◽  
Vol 11 (1) ◽  
pp. 1-1
Author(s):  
Eirini Liotou
Keyword(s):  
Quality Of Service ◽  
Cellular Networks ◽  
User Experience ◽  
Quality Of Experience ◽  
Specific Service ◽  
Mobile Cellular ◽  
Mobile Cellular Networks ◽  
Requirements Quality ◽  
Phd Thesis

Traditionally, previous generations of mobile cellular networks have been designed with Quality of Service (QoS) criteria in mind, so that they manage to meet specific service requirements. Quality of Experience (QoE) has, however, recently emerged as a concept, disrupting the design of future network generations by giving clear emphasis on the actually achieved user experience.

scholarly journals Analysis of the Cost of Varying Levels of User Perceived Quality for Internet Access

2020 ◽  
Author(s):  
Ali Adib Arnab ◽  
John Schormans ◽  
Sheikh Razibulhasan Raj ◽  
Nafi Ahmad
Keyword(s):  
Quality Of Service ◽  
User Experience ◽  
Quality Of Experience ◽  
Internet Access ◽  
End User ◽  
Opinion Score ◽  
Commercial Organizations ◽  
The Cost ◽  
Qos Metrics

Quality of Service (QoS) metrics deal with network quantities, e.g. latency and loss, whereas Quality of Experience (QoE) provides a proxy metric for end-user experience. Many papers in the literature have proposed mappings between various QoS metrics and QoE. This paper goes further in providing analysis for QoE versus bandwidth cost. We measure QoE using the widely accepted Mean Opinion Score (MOS) rating. Our results naturally show that increasing bandwidth increases MOS. However, we extend this understanding by providing analysis for internet access scenarios, using TCP, and varying the number of TCP sources multiplexed together. For these target scenarios our analysis indicates what MOS increase you get by further expenditure on bandwidth. We anticipate that this will be of considerable value to commercial organizations responsible for bandwidth purchase and allocation.

scholarly journals Delivering User Experience over Networks: Towards a Quality of Experience Centered Design Cycle for Improved Design of Networked Applications

2021 ◽  
Vol 2 (6) ◽  
Author(s):  
Anika Seufert ◽  
Svenja Schröder ◽  
Michael Seufert
Keyword(s):  
User Experience ◽  
Development Process ◽  
Quality Of Experience ◽  
Smartphone Application ◽  
The Internet ◽  
Human Centered Design ◽  
Design Cycle ◽  
Improved Design ◽  
Application Developers

AbstractTo deliver the best user experience (UX), the human-centered design cycle (HCDC) serves as a well-established guideline to application developers. However, it does not yet cover network-specific requirements, which become increasingly crucial, as most applications deliver experience over the Internet. The missing network-centric view is provided by Quality of Experience (QoE), which could team up with UX towards an improved overall experience. By considering QoE aspects during the development process, it can be achieved that applications become network-aware by design. In this paper, the Quality of Experience Centered Design Cycle (QoE-CDC) is proposed, which provides guidelines on how to design applications with respect to network-specific requirements and QoE. Its practical value is showcased for popular application types and validated by outlining the design of a new smartphone application. We show that combining HCDC and QoE-CDC will result in an application design, which reaches a high UX and avoids QoE degradation.

scholarly journals Assessment of quality of experience (QoE) of image compression in social cloud computing

2018 ◽  
Vol 14 (2) ◽  
pp. 125-143 ◽  
Author(s):  
Asif Ali Laghari ◽  
Hui He ◽  
Muhammad Shafiq ◽  
Asiya Khan
Keyword(s):  
Cloud Computing ◽  
Image Compression ◽  
Quality Of Experience ◽  
Social Cloud

scholarly journals Image Quality in Augmented Binocular Vision: QoE Approximations with QoS and EEG

2017 ◽  
Vol 61 (4) ◽  
pp. 327 ◽  
Author(s):  
Patrick Seeling
Keyword(s):  
Quality Of Service ◽  
Image Quality ◽  
Augmented Reality ◽  
Binocular Vision ◽  
Quality Of Experience ◽  
Reference Data ◽  
Ground Truth ◽  
Data Set ◽  
Gamma Frequency

Augmented reality (AR) applications become increasingly popular, however, little is known about how multimedia consumption interplays with the Quality of Experience (QoE) in these settings. We experimentally evaluate binocular vision augmentation with optical see-through devices by contrasting QoE, expressed by Mean Opinion Scores (MOS), with a ground truth reference data set. We find that the QoE in AR settings (i) is higher for small media impairments and lower for high impairment levels compared to opaque settings, (ii) exhibits an emerging quantifiable relationship with the QoE in traditional setups, (iii) can be approached with common objective image quality metrics as Quality of Service (QoS) factors, and (iv) exhibits a relationship between the Low Gamma frequency band levels determined with consumer-grade electroencephalograms (EEG) and image quality levels as rated by the participants.

Introduction

2010 ◽  
pp. 1-13 ◽  
Author(s):  
Sasan Adibi ◽  
Raj Jain ◽  
Shyam Parekh ◽  
Bell Labs
Keyword(s):  
Wireless Networks ◽  
Quality Of Service ◽  
User Experience ◽  
Quality Of Experience ◽  
Mobile Services ◽  
Network Resources ◽  
Acceptable Quality ◽  
New Challenges

Emergence of all IP based wired and wireless networks for mobile services, calls for new innovations and architectural approaches. Coexistence of legacy and emerging networks such as different generations of networks based on 3GPP and 3GPP2 specifications, Wi-Fi and WiMAX, have posed new challenges to guarantee acceptable Quality of Experience (QoE) to the users. Different user environments such as fixed, nomadic, and vehicular have brought about new Quality of Service (QoS) practices and have introduced policies to best optimize the network resources and enhance user experience.

Sign in / Sign up

Export Citation Format

Share Document