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QoE Modelling, Measurement and Prediction: A Review
In mobile computing systems, users can access network services anywhere and
anytime using mobile devices such as tablets and smart phones. These devices
connect to the Internet via network or telecommunications operators. Users
usually have some expectations about the services provided to them by different
operators. Users' expectations along with additional factors such as cognitive
and behavioural states, cost, and network quality of service (QoS) may
determine their quality of experience (QoE). If users are not satisfied with
their QoE, they may switch to different providers or may stop using a
particular application or service. Thus, QoE measurement and prediction
techniques may benefit users in availing personalized services from service
providers. On the other hand, it can help service providers to achieve lower
user-operator switchover. This paper presents a review of the state-the-art
research in the area of QoE modelling, measurement and prediction. In
particular, we investigate and discuss the strengths and shortcomings of
existing techniques. Finally, we present future research directions for
developing novel QoE measurement and prediction technique
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Intelligent multimedia communication for enhanced medical e-collaboration in back pain treatment
This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2004 SAGE PublicationsRemote, multimedia-based, collaboration in back pain treatment is an option which only recently has come to the attention of clinicians and IT providers. The take-up of such applications will inevitably depend on their ability to produce an acceptable level of service over congested and unreliable public networks. However, although the problem of multimedia application-level performance is closely linked to both the user perspective of the experience as well as to the service provided by the underlying network, it is rarely studied from an integrated viewpoint. To alleviate this problem, we propose an intelligent mechanism that integrates user-related requirements with the more technical characterization of quality of service, obtaining a priority order of low-level quality of service parameters, which would ensure that user-centred quality of perception is maintained at an optimum level. We show how our framework is capable of suggesting appropriately tailored transmission protocols, by incorporating user requirements in the remote delivery of e-health solutions
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