QoE Model Driven for Network Services

2010

In the last decade, networks have evolved from simple data packet forwarding to platforms that support complex multimedia services, such as network-based personal video recording and broadcast TV. Each of these services has significant quality demands: they are very sensitive to packet loss and jitter, and require a substantial amount of bandwidth. As the quality perceived by the end user gives the most accurate view on the streamed service quality, operators are increasing their focus on this type of metric, commonly described as Quality of Experience. This paper presents the design of a Quality of Experience information model that defines important metrics for measuring service quality. Based on these metrics, we define a novel control loop that represents the relationships among Quality of Experience, the Customer, and network services.

SPIE Newsroom, 2013

We are witnessing a number of paradigm shifts in many Information and Communication Technology (ICT) areas. 5G, Future Internet and very high resolution digital TV defined a new vision of services with novel approaches to their implementation, deployment and operation based on concepts of Software Defined Network (SDN) and Network Function Virtualization (NFV). Increasing transmission capabilities in both mobile and fixed networks became an enabler for a new generation of multimedia services and applications. Evolution of digital video technology and competition of operator supported services with Over The Top (OTT) applications caused change in understanding of Quality of Service (QoS) and Quality of Experience (QoE) concepts. This paper surveys the change of QoE approaches and interpretation in the context of new services and applications.

IEEE Wireless Communications, 2015

Journal of Computer and Communications, 2020

This paper investigates the subjective assessment of QoE of web and video services over a mobile network. To achieve this, the authors used the network emulator (NetEm) traffic control functionality to simulate the dynamic behaviour of a mobile network. Experiments were conducted in a laboratory setting and test conditions were varied to ascertain the QoE, with a focus on QoE metrics such as delay and packet loss ratio. From the experiments conducted, it was observed that there was a negative correlation between delay and average mean opinion score (MOS), and between packet loss ratio and average MOS. The results obtained can be adopted by network operators to provide better services which would lead to improved subscriber base and profitability for the operators and better QoE for the end users.

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2013

Web applications are becoming the key services in today's networks (both fixed networks and mobile networks). Consideration of web service quality has become essential to provide the end users with satisfying Quality of Experience (QoE). In order to evaluate and manage the web quality, methods for QoE assessment are desired to estimate the service quality perceived by the end users. In this paper, we study a number of existing objective quality assessment models for assessing the QoE of web applications, and compare their performance with simulations to find out their individual advantages and limitations to use in practice. Simulation results show that the proposed QoE model can be applied for evaluating the quality of different web sources in the Long Term Evolution (LTE) networks, considering the lossy property of mobile networks. A fitting model is presented to describe the correlation between network Quality of Service and User QoE obtained in subjective lab test. To overcome the shortcomings of the existing models, this paper also proposes an enhanced QoE model which considers the effects of parameters such as page download size and content, browser cache setting as well as the packet losses and connection throughput in quality assessment e.g., page response time. To study other user related aspects in the evaluation of QoE, subjective tests in real systems and environments are planned as the next step.

2012

Quality of Experience (QoE) is emerging as the holy grail of human-centric multimedia services. QoE is a multi-disciplinary field based on social psychology, cognitive science, economics and engineering science, focused on understanding overall human quality of experience requirements. QoE has been viewed as the pivotal set of metrics in determining the success or failure of any product or service. In real time environment, QoE is influenced by multiple service factors such as application and network level QoS ...

Quality of Service and Solutions, 2009

This chapter discusses the quality assurance of multimedia services over IP networks from the end user standpoint and introduces the concept of quality of experience (QoE). The discussion of quality assurance includes aspects that range from the network and application layers to the end user perspective. The focus of the discussion presented in this chapter is oriented to the video services delivery that can be considered a significant evolution of services providers' portfolio. This chapter presents quality requirements for video and TV services and performance measures that focuses on the quality perceived by the end user. This approach is broader than that oriented to quality of service (QoS), which focuses on the performance measures from the network perspective. QoE takes into account how well a service meet customers goals and expectations rather than focusing only on the network performance.

annals of telecommunications - annales des télécommunications, 2009

The impact of network performance on user experience is important to know, as it determines the success or failure of a service. Unfortunately, it is very difficult to assess it in real-time on an operational network. Monitoring of network-level performance criteria is easier and more usual. But the problem is then to correlate these network-level Quality of Service (QoS) to the Quality of Experience (QoE) perceived by the users. Efforts have been done in the previous years to map user behaviour to traffic characteristics on the network to QoS. However, being able to successfully relate these traffic characteristics to user satisfaction is not a simple task and still requires further investigations. In this work, we try to associate on one side the correlations between various traffic characteristics measured on an operational network and on the other side the user experience tested on an experimental platform. Our aim is to observe some pronounced trends regarding relationships between both types of results. More precisely, we want to validate how and to what extent the volumes of user sessions represent the level of user satisfaction. Along this way, we need to revise classical relationships between some of the network performance indicators such as loss, download time and throughput in order to strengthen the understanding of this impact on each other and on user satisfaction. This preliminary study is based on the application web.

Journal of University of Human Development, 2016

In recent years, multimedia services and social media applications have become extremely popular as they have been accessed by laptop computers and mobile devices. These can be considered as basic communications functionalities required for building e-society. The heterogeneity of hardware capabilities and network environments result in big challenges for service providers in always providing users with a satisfying experience. The meaning of Quality of Experience (QoE) reflects the degree of a user's subjective satisfaction, which can be different from the Quality of Service (QoS) concept as QoS is solely related to objective system performance metrics, such as the bandwidth, delay, and loss rate. In this work, we propose a general approach for improving QoE through QoS such as to support various e-society applications and services. Various models and parameters related to this issue are reviewed. The proposal represents a framework that considers different aspects such as classification, marking, routing, and queuing to achieve better controlling of relative QoS parameters.