Mobile Internet and mobile services that make use of mobile data are increasingly popular. However, the cost of content delivery, in particular, multimedia type content over cellular networks is still high and poses a challenge for some users who are not necessarily willing or cannot afford to pay too much for it. The problem is further exacerbated when video content is used, as this type of content is heavier and can lead to higher bills. In this context, this paper presents a novel cost-oriented adaptive multimedia delivery (COMEDY) mechanism that considers the user's willingness to pay for a certain video quality and user's mobile device characteristics to deliver adaptive multimedia content over wireless connection. The goal of the mechanism is to reduce the cost of multimedia delivery for users that are not willing to pay that much. The mechanism is evaluated both through objective and subjective studies. The evaluation shows that the proposed mechanism provides a reduction in the price paid for accessing multimedia content, and the user's perceived quality is not negatively affected.Index Terms-Adaptive multimedia, cost of multimedia delivery, mobile data billing plans, mobile devices.

Abstract-As mobile devices are becoming more compact and powerful and as they start to be increasingly used for accessing power-hungry multimedia streaming applications, there is an increasing need for mechanisms to efficiently manage the limited battery power resources. This is especially important as the battery capacity has not kept up with the power requirements of an increasing number of mobile device features and "always on" connected users. Adaptive multimedia-based power-saving mechanisms often decrease the clip bitrate to increase the mobile device battery life, without considering the effect of these degradations on the user-perceived quality. This paper proposes BitDetect, a mechanism that uses objective video quality assessment metrics to detect content-specific video bitrate levels that enable saving battery power while maintaining good user perceived quality. Results from a subjective study indicate that the recommended bitrate offers good user-perceived quality across different multimedia clips. Furthermore, experimental tests indicate that significant battery power can be saved by using the recommended bitrates when streaming multimedia clips to a mobile device.Index Terms-Battery power saving, bitrate estimation, objective assessment metrics, subjective video quality assessment.

-With the advances in mobile technologies, smart mobile computing devices have become increasingly affordable and powerful, leading to a significant growth in both the number of advanced mobile users and their bandwidth demands. Moreover multimedia streaming to these high-end mobile devices has become widespread. However, multimedia applications are known to be resource-hungry and in order to cope with this explosion of data traffic, operators have started deploying different, overlapping radio access network technologies. One important challenge in such a heterogeneous wireless environment is to ensure an Always Best Experience to the mobile user, anywhere and anytime. This paper proposes the Quality Utility, a realistic mapping function of the received bandwidth to user satisfaction for multimedia streaming applications. The Quality Utility is mapped to a Google Nexus One Android Mobile device and validated through objective and subjective tests.

Abstract-Multimedia users are becoming increasingly quality-aware as the technological advances make ubiquitous the creation and delivery of high-definition multimedia content. While much research work has been conducted on multimedia quality assessment, most of the existing solutions come with their own limitations, with particular solutions being more suitable to assess particular aspects related to user's Quality of Experience (QoE). In this context, there is an increasing need for innovative solutions to assess user's QoE with multimedia services. This paper proposes the QoE-EEG-Analyser that provides a solution to automatically assess and quantify the impact of various factors contributing to user's QoE with multimedia services. The proposed approach makes use of participant's frustration level measured with a consumer-grade EEG system, the Emotiv EPOC. The main advantage of QoE-EEG-Analyser is that it enables continuous assessment of various QoE factors over the entire testing duration, in a non-invasive way, without requiring the user to provide input about his perceived visual quality. Preliminary subjective results have shown that frustration can indicate user's perceived QoE.Index Terms-Quality of Experience, multimedia quality assessment, subjective assessment methods, objective quality metrics, EEG.

The reliable estimation of video quality has become increasingly important with the proliferation of online video services and users becoming more quality aware. A multitude of objective video quality assessment (VQA) metrics with various performance and complexity have been proposed. However, their applicability in real-world scenarios is limited by the lack of clear interpretations of how the metric values reflect the subjective user-perceived video quality. This paper proposes a novel mechanism called VQAMap, that uses data from public VQA databases and enables to automatically create generic rules for mapping the values of objective VQA metrics to the subjective MOS scale (i.e., 1 -bad, 2 -poor, 3 -fair, 4 -good, and 5 -excellent). An extensive evaluation study of VQAMap was conducted using data from three public VQA databases, considering six objective VQA metrics. The results analysis has shown that VQAMap provides mapping rules with quality estimation accuracy as high as 95%, while the variation in performance being caused by the varying accuracy of the different objective metrics.Index Terms-Video quality assessment (VQA), mean opinion score (MOS), subjective methods, objective metrics, video quality mapping, performance evaluation, public video quality databases.

Abstract-As mobile devices are becoming more powerful and affordable they are increasingly used for mobile learning activities. By enabling learners' access to educational content anywhere and anytime, mobile learning has both the potential to provide online learners with new opportunities, and to reach less privileged categories of learners that lack access to traditional e-learning services. Among the many challenges with mobile learning, the battery-powered nature of mobile devices and in particular their limited battery life, stands out as one issue that can significantly limit learners' access to educational content while on the move. Adaptation and personalisation solutions have widely been considered for overcoming the differences between learners and between the characteristics of their mobile devices. However, while various energy saving solutions have been proposed in order to provide mobile users with extended device usage time, the areas of adaptive mobile learning and energy conservation in wireless communications failed to meet under the same umbrella. This paper bridges the two areas by presenting an overview of adaptive mobile learning systems as well as how these can be extended to make them energy-aware. Furthermore, the paper surveys various approaches for energy measurement, modelling and adaptation, three major aspects that have to be considered in order to deploy energy-aware mobile learning systems. Discussions on the applicability and limitations of these approaches for mobile learning are also provided.

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