Khalil ur Rehman Laghari

Toward total quality of experience: A QoE model in a communication ecosystem

In recent years, the quality of experience notion has become a major research theme within the telecommunications community. QoE is an assessment of the human experience when interacting with technology and business entities in a particular context. A communication ecosystem encompasses various domains such as technical aspects, business models, human behavior, and context. For each aspect of a communication ecosystem, various models have been developed. However, few models have been designed to integrate all aspects of a communication ecosystem to understand human behavioral needs in a detailed and structured way. While existing models have produced the basic sketch of QoE modeling, more concepts and interdomain mapping are to be incorporated in order to have a clear picture of QoE in communication ecosystems. The aim of the current work is to build on the existing research being conducted in disparate disciplines about human behavior in order to provide a high-level model that can be adapted to many specific contexts and to encourage future research which examines these crossdomain relationships.

QoE Aware Service Delivery in Distributed Environment

Service delivery and customer satisfaction are strongly related items for a correct commercial management platform. Technical aspects targeting this issue relate to QoS parameters that can be handled by the platform, at least partially. Subjective psychological issues and human cognitive aspects are typically unconsidered aspects and they directly determine the Quality of Experience (QoE). These factors finally have to be considered as key input for a successful business operation between a customer and a company. In our work, a multi-disciplinary approach is taken to propose a QoE interaction model based on the theoretical results from various fields including pyschology, cognitive sciences, sociology, service ecosystem and information technology. In this paper a QoE evaluator is described for assessing the service delivery in a distributed and integrated environment on per user and per service basis.

Approaches to understanding the impact of technologies for aging in place: a mini-review.

Background: There are many approaches to evaluating aging-in-place technologies. While there are standard measures for outcomes such as health and caregiver burden, which lend themselves to statistical analysis, researchers have a harder time identifying why a particular information and communication technology (ICT) intervention worked (or not). Objective: The purpose of this paper is to review a variety of methods that can help answer these deeper questions of when people will utilize an ICT for aging in place, how they use it, and most importantly why. This review is sensitive to the special context of aging in place, which necessitates an evaluation that can explore the nuances of the experiences of older adults and their caregivers with the technology in order to fully understand the potential impact of ICTs to support aging in place. Methods: The authors searched both health (PubMed) and technology (ACM Digital Library) venues, reviewing 115 relevant papers that had an emphasis on understanding the use of aging-in-place technologies. This mini-review highlights a number of popular methods used in both the health and technology fields, including qualitative methods (e.g. interviews, focus groups, contextual observations, diaries, and cultural probes) and quantitative methods (e.g. surveys, the experience sampling method, and technology logs). Results: This review highlights that a single evaluation method often is not adequate for understanding why people adopt ICTs for aging in place. The review ends with two examples of multifaceted evaluations attempting to get at these deeper issues. Conclusion: There is no proscriptive formula for evaluating the intricate nuances of technology acceptance and use in the aging-in-place context. Researchers should carefully examine a wide range of evaluation techniques to select those that will provide the richest insights for their particular project.

QoM: A new quality of experience framework for multimedia services

Quality of Experience (QoE) provides human centric assessment of multimedia quality. QoE of a multimedia service is affected by various application and network layer QoS parameters; content and business parameters. In this paper, we propose a new QoE framework for Multimedia services (named as QoM) for run time quality evaluation of video streaming services based on the influence of QoE factors, various network and application level QoS parameters. The newly proposed QoM framework monitors QoS and QoE data, evaluates it and moreover, in the event of decline in QoE, it can also send alert messages to the Administrator based on some policy rules. Our new QoM framework is being launched as an open-source QoE evaluation tool for the industry and research community. More realistic experimental work is also underway and we intend to conduct user tests to evaluate the performance of the proposed QoM framework in a context of real 4G WiMax wireless networks.

Quantitative and qualitative assessment of QoE for multimedia services in wireless environment

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 parameters, content, and business aspects. We emulate wireless environment and analyze the combined impact of the network and application level QoS parameters and content characteristics over user perceived quality for video streaming service. We use Rough Set Theory (RST) for quantitative assessment and simple CCA frame work for qualitative assessment of user data in order to understand the influence of multiple multimedia service parameters over QoE.

Are QoE Requirements for Multimedia Services Different for Men and Women? Analysis of Gender Differences in Forming QoE in Virtual Acoustic Environments

In recent years, the Quality of Experience (QoE) notion has become a major research theme within the telecommunication community. QoE provides an assessment around a human perception, feeling, performance and behavior. Normally, research studies on multimedia, Quality of Experience (QoE) and gender differences are carried out separately. To develop multimedia solutions covering QoE aspects, keeping the gender differences in mind, are the need of time. In current study, we are interested in knowing how QoE is shaped in Virtual Acoustic Environment (VAE) for male and female. We present experimental test results which provide interesting findings that both male and female have difference in their performance and perception in locating concurrent talkers in small and big sized virtual conferencing rooms. The middle-sized virtual room was suitable for teleconferencing because both male and female participants’ performance and perception converge to similar trend and obtained better QoE values.

Towards a service delivery based on customer eXperience ontology: shift from service to eXperience

Customer eXperience is a blue print of customer requirements. In this era of heightened competition and volatile global economy, delivering services originating from diverse sources, without satisfying thorough customer experience practices may increase customer dissatisfaction, and churn rate. In order to guarantee rich customer experience, the service delivery mechanism should shift towards customer experience centric approach. This shift from service to experience brings customer in the driving seat, whose intentions and needs trigger service delivery. This paper introduces ontological model for customer experience, intended for use in run time environments by policy based management systems, to initiate and enable service delivery based on customer experience. The work presented here can have valuable implications for future studies of customer experience based service delivery approach.