Abstract. When today's commuters in the train or in a car want to access the Internet, they see themselves restricted to simple web surfing or e-mail. Interactive multimedia services, like online gaming or video conferencing are still unavailable to them, even with promising new technologies like UMTS or WiMAX. The impact of high bit rate multimedia traffic on the access network and aggregation network is an important topic, that has not been addressed in enough detail before. We designed a network architecture for offering these multimedia services to fast moving users. We refer to the overall network architecture as the FAMOUS network architecture, which consists of two parts: (i) an access network part which has to deal with large number of users, asking for a high bandwidth, while experiencing a high handoff frequency and (ii) an aggregation network part which has to deal with dynamic tunnels of very high bandwidth, while experiencing a low handoff frequency. In this paper, we detail the FAMOUS architecture, together with optimized handoff strategies, an optical switching architecture, a design methodology for dimensioning aggregations networks and automatic tunnel pre-configuration and activation. Moreover, performance results of these mentioned aspects will be presented.

Internet-on-the-train is a rising concept in the last few years. Several trials in different countries have proved the feasibility of offering Internet access to train commuters, but none of them combines broadband access, scalability, seamless handover and quality of service guarantees in one solution. In this paper, we propose a new architecture to satisfy these needs. Using real handover measurement data of several common broadband wireless technologies, we compare two possible inter-working mobility solutions: Mobile Multi-Path SCTP (MMP-SCTP) and Mobile IP (MIP).

User satisfaction is a key factor in the success of novel multimedia services. Yet, to enable service providers and network operators to control and maximize the quality (QoS, QoE) of delivered video streams, quite some challenges remain. In this paper, we particularly focus on three of them. First of all, objectively measuring video quality requires appropriate quality metrics and methods of assessing them in a real-time fashion. Secondly, the recent Scalable Video Coding (SVC) format opens opportunities for adapting video to the available (network) resources, yet the appropriate configuration of video encoding as well as real-time streaming adaptation are largely unaddressed research areas. Thirdly, while bandwidth reservation mechanisms in access/core networks do exist, service providers lack a means for guaranteeing QoS in the increasingly complex home networks (which they are not in full control of). In this paper we offer a broad view on these interrelated issues, by presenting the developments originating in a Flemish research project (including proof-of-concept demonstrations). From a developmental perspective, we propose an architecture combining a real-time video quality monitoring platform, on-thefly adaptation (optimizing the video quality) and QoS reservation in a heterogeneous home network based on UPnP QoS v3. From a research perspective, we propose a new subjective test procedure that revealed user preference for temporal scalability over quality scalability. In addition, an extensive study on optimizing HD SVC encoding in IPTV scenarios with fluctuating bandwidth showed that under certain bandwidth constraints (prohibiting sufficient fidelity) spatial scalability is a better option than quality scalability.

Rare germline pathogenic TP53 missense variants often predispose to a wide spectrum of tumors characterized by Li-Fraumeni syndrome (LFS) but a subset of variants is also seen in families with exclusively hereditary breast cancer (HBC) outcomes. We have developed a logistic regression model with the aim of predicting LFS and HBC outcomes, based on the predicted effects of individual TP53 variants on aspects of protein conformation. A total of 48 missense variants either unique for LFS (n = 24) or exclusively reported in HBC (n = 24) were included. LFS-variants were over-represented in residues tending to be buried in the core of the tertiary structure of TP53 (p = 0.0014). The favored logistic regression model describes disease outcome in terms of explanatory variables related to the surface or buried status of residues as well as their propensity to contribute to protein compactness or protein-protein interactions. Reduced, internally validated models discriminated well between LFS and HBC (C-statistic = 0.78−0.84; equivalent to the area under the ROC (receiver operating characteristic) curve), had a low risk for over-fitting and were well calibrated in relation to the known outcome risk. In conclusion, this study presents a phenotypic prediction model of LFS and HBC risk for germline TP53 missense variants, in an attempt to provide a complementary tool for future decision making and clinical handling.

No abstract