Abstract
Wireless sensor networks (WSNs) may be made of a large amount of small devices that are able to sense changes in the environment, and communicate these changes throughout the network. An example of a similar network is a photo voltaic (PV) power plant, where there is a sensor connected to each solar panel. The task of each sensor is to sense the output of the panel which is then sent to a central node for processing. As the network grows, it becomes impractical and even impossible to configure all these nodes manually. And so, the use of self-organization and auto-configuration algorithms becomes essential. In this paper, three algorithms are proposed that allow nodes in the network to automatically identify their closest neighbors, relative location in the network, and select which frequency channel to operate in. This is done using the value of the Received Signal Strength Indicator (RSSI) of the messages sent and received during the setup phase. The performance of these algorithms is tested by means of both simulations and testbed experiments. Results show that the error in the performance of the algorithms decreases as we increase the number of RSSI values used for decision making. Additionally, the number of nodes in the network affects the setup error. However, the value of the error is still acceptable even with a high number of nodes.

Abstract
A common problem in networking research and development is the duplicate effort of writing simulation and implementation code of network protocols. This duplication can be avoided through the use of fast prototyping development processes, which enable reusing simulation code in real prototyping and in production environments. Although this functionality is already available by using ns-3 emulation, there are still limitations regarding the additional packet processing that emulation introduces, which degrades the node’s performance and limits the amount of network traffic that can be processed. In this paper we propose an approach to reduce the performance problem associated with fast prototyping that consists in migrating data plane operations processing to outside of ns-3. In a well-designed network, most of the traffic should be data. By moving the data plane operations outside of ns-3 the overhead associated with this kind of traffic is greatly reduced, while control plane protocols may still be reused. In order to validate our proposed solution, we extended the Wireless Metropolitan Routing Protocol (WMRP) and Optimized Link State Routing (OLSR) protocols to use the developed architecture, tested their performance in real environments, and verified the amount of code reuse between the simulator and the real system.

Abstract
Multimedia content has the potential for significant impact on users’ emotions, their sense of presence and engagement experiencing the service, application or information being provided, in immersive environments. The evolution of technology, user expectations and results from research activities have led to an enormous increase in the amount of content delivered in different formats, via a number of heterogeneous communication networks, to a range of devices, many of them portable and offering tremendous opportunities for immersion, user participation and personalization. New paradigms for media production, distribution and consumption have been emerging, introducing different sensory modalities and audio-visual surround effects, for an increased sense of presence, and also enabling participation and social interaction in the media chain, thus increasing the sense of belonging and contributing to the success of the services being provided

Abstract
The design, manufacture and operational characteristics (e.g., yield, performance, and reliability) of modern electronic integrated systems exhibit extreme levels of complexity that cannot be easily modelled or predicted. Different mathematical methodologies have been explored to address this issue. Monte Carlo simulation is the most widely employed and straightforward approach to evaluate the circuits' performance statistics. However, the high number of trial cases and the long simulations times required to obtain results for complex circuits with a ppm resolution, lead to very long analysis times. The present work addresses the evaluation of alternative statistical inference methodologies which allow obtaining similar results departing from a smaller dimension data set of Monte Carlo simulations from which the overall population is estimated. These methodologies include the use of Bayesian inference, Expectation-inimization, and Kolmogorov-Smirnov tests. Results are presented which show the validity of these approaches.

Abstract
A new methodology for fault detection on wearable medical devices is proposed. The basic strategy relies on correctly classifying the captured physiological signals, in order to identify whether the actual cause is a wearer health abnormality or a system functional flaw. Data fusion techniques, namely fuzzy logic, are employed to process the physiological signals, like the electrocardiogram (ECG) and blood pressure (BP), to increase the trust levels of the captured data after rejecting or correcting distorted vital signals from each sensor, and to provide additional information on the patient's condition by classifying the set of signals into normal or abnormal condition (e.g. arrhythmia, chest angina, and stroke). Once an abnormal situation is detected in one or several sensors the monitoring system runs a set of tests in a fast and energy efficient way to check if the wearer shows a degradation of his health condition or the system is reporting erroneous values.

Abstract
This article addresses the design, development, and evaluation of T-shirt prototypes that embed novel textile sensors for the capture of cardio and respiratory signals. The sensors are connected through textile interconnects to either an embedded custom-designed data acquisition and transmission unit or to snap fastener terminals for connection to external monitoring devices. The performance of the T-shirt prototype is evaluated in terms of signal-to-noise ratio amplitude and signal interference caused by baseline wander and motion artefacts, through laboratory tests with subjects in standing and walking conditions. Performance tests were also conducted in a hospital environment using a T-shirt prototype connected to a commercial three-channel Holter monitoring device. The textile sensors and interconnects were realized with the assistance of an industrial six-needle digital embroidery tool and their resistance to wear addressed with normalized tests of laundering and abrasion. The performance of these wearable systems is discussed, and pathways and methods for their optimization are highlighted.