How to make classrooms creative and open spaces: ARIS games, digital artifacts and storytelling

As part of long-term research into interviewing users and visualizing digital artifacts, we have created a parallel archives of projects in our classroom. Ethnography helps us to discover the temporal trends of interactions with students and with the virtual environment. The outcomes expected motived us to repurpouse stories we co-create with students in a new form, retelling motivations, design, narratives, into a gaming scenario where the use of experiences become more digital and less tangible but always snapshots of their social existence.Peer Reviewe

Integrating peer-to-peer functionalities and routing in mobile ad-hoc networks

Mobile Ad-hoc Networks (MANETs) impose strict requirements in terms of battery life, communication overhead and network latency, therefore optimization should be made to applications and services such as domain name service (DNS), dynamic host configuration protocol (DHCP) and session initiation protocol (SIP) if they are to be considered for use on MANETs. Due to the decentralized and self-organizing nature of MANETs, such applications could utilize a distributed name resolution/data storage service. Distributed Hash Tables (DHTs) enable these features by virtually organizing the network topology in a peer-to-peer (P2P) overlay. P2P overlays have been designed to operate on the application layer without knowledge of the underlying network thus causing poor performance. To address this problem, we propose and evaluate two different DHTs integrated with MANET routing in order to optimize the overall performance of MANET communications when P2P applications and services are used. Both architectures share the same functionality such as decentralization, self-reorganization, and self-healing but differ in MANET routing protocol. Performance evaluation using the NS2 simulator shows that these architectures are suited to different scenarios namely increasing network size and peer velocity. Comparisons with other well-known solutions have proven their efficiency with regard to the above requirements

Energy Savings for Cellular Network with Evaluation of Impact on Data Traffic Performance

We present a concrete methodology for saving energy in future and contemporary cellular networks. It is based on re-arranging the user-cell association so as to allow shutting down under-utilized parts of the network. We consider a hypothetical static case where we have complete knowledge of stationary user locations and thus the results represent an upper bound of potential energy savings. We formulate the problem as a binary integer programming problem, thus it is NP-hard, and we present a heuristic approximation method. We simulate the methodology on an example real cellular network topology with traffic- and user distribution generated according to recently measured patterns. Further, we evaluate the energy savings, using realistic energy profiles, and the impact on the user-perceived network performance, represented by delay and throughput, at various times of day. The general findings conclude that up to 50% energy may be saved in less busy periods, while the performance effects remain limited. We conclude that practical, real-time user-cell re-allocation methodology, taking into account user mobility predictions, may thus be feasible and bring significant energy savings at acceptable performance impact

BARI+: A Biometric Based Distributed Key Management Approach for Wireless Body Area Networks

Wireless body area networks (WBAN) consist of resource constrained sensing devices just like other wireless sensor networks (WSN). However, they differ from WSN in topology, scale and security requirements. Due to these differences, key management schemes designed for WSN are inefficient and unnecessarily complex when applied to WBAN. Considering the key management issue, WBAN are also different from WPAN because WBAN can use random biometric measurements as keys. We highlight the differences between WSN and WBAN and propose an efficient key management scheme, which makes use of biometrics and is specifically designed for WBAN domain

Video Quality Prediction for Video over Wireless Access Networks (UMTS and WLAN)

Transmission of video content over wireless access networks (in particular, Wireless Local Area Networks (WLAN) and Third Generation Universal Mobile Telecommunication System (3G UMTS)) is growing exponentially and gaining popularity, and is predicted to expose new revenue streams for mobile network operators. However, the success of these video applications over wireless access networks very much depend on meeting the user’s Quality of Service (QoS) requirements. Thus, it is highly desirable to be able to predict and, if appropriate, to control video quality to meet user’s QoS requirements. Video quality is affected by distortions caused by the encoder and the wireless access network. The impact of these distortions is content dependent, but this feature has not been widely used in existing video quality prediction models. The main aim of the project is the development of novel and efficient models for video quality prediction in a non-intrusive way for low bitrate and resolution videos and to demonstrate their application in QoS-driven adaptation schemes for mobile video streaming applications. This led to five main contributions of the thesis as follows:(1) A thorough understanding of the relationships between video quality, wireless access network (UMTS and WLAN) parameters (e.g. packet/block loss, mean burst length and link bandwidth), encoder parameters (e.g. sender bitrate, frame rate) and content type is provided. An understanding of the relationships and interactions between them and their impact on video quality is important as it provides a basis for the development of non-intrusive video quality prediction models.(2) A new content classification method was proposed based on statistical tools as content type was found to be the most important parameter. (3) Efficient regression-based and artificial neural network-based learning models were developed for video quality prediction over WLAN and UMTS access networks. The models are light weight (can be implemented in real time monitoring), provide a measure for user perceived quality, without time consuming subjective tests. The models have potential applications in several other areas, including QoS control and optimization in network planning and content provisioning for network/service providers.(4) The applications of the proposed regression-based models were investigated in (i) optimization of content provisioning and network resource utilization and (ii) A new fuzzy sender bitrate adaptation scheme was presented at the sender side over WLAN and UMTS access networks. (5) Finally, Internet-based subjective tests that captured distortions caused by the encoder and the wireless access network for different types of contents were designed. The database of subjective results has been made available to research community as there is a lack of subjective video quality assessment databases.Partially sponsored by EU FP7 ADAMANTIUM Project (EU Contract 214751