Measuring and predicting the user's Quality of Experience (QoE) of a multimedia stream is the first step towards improving and optimizing the provision of mobile streaming services. This enables us to better understand how Quality of Service (QoS) parameters affect service quality, as it is actually perceived by the end user. Over the last years this goal has been pursued by means of subjective tests and through the analysis of the user's feedback. Existing statistical techniques have lead to poor accuracy (order of 70%) and inability to evolve prediction models with the system's dynamics. In this paper, we propose a novel approach for building accurate and adaptive QoE prediction models using Machine Learning classification algorithms, trained on subjective test data. These models can be used for real-time prediction of QoE and can be efficiently integrated into online learning systems that can adapt the models according to changes in the environment. Providing high accuracy of above 90%, the classification algorithms become an indispensible component of a mobile multimedia QoE management system
The Third Generation Mobile Network aims at providing present and future Internet services everywhere and at anytime using cellular technologies. This is based on its all-IP core network known as the IP Multimedia Subsystem which provides end-users with better QoS, charging and integration of different services. However, certain interoperability and interconnectivity limitations still exist, indicating that the convergence of the Internet and 3G networks is still not complete. We provide a prototype-based evaluation on the signalling interworking of end-toend services across the networks. Our results show crucial performance shortcomings of the standardised approach which requires immediate attention.
The IP multimedia subsystem (IMS) specifies a service centric framework for converged, all-IP networks. This promises to provide the long awaited environment for deploying technology-neutral services over fixed, wireless, and cellular networks, known as third generation (3G) networks. Since its initial proposal in 1999, the IMS has gone through different stages of development, from its initial Release 5 up to the current Release 7.
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