Co-simulazione e co-progetto non lineare/elettromagnetico di sistemi wireless non convenzionali

L’attività di ricerca contenuta in questa tesi si è concentrata nello sviluppo e nell’implementazione di tecniche per la co-simulazione e il co-progetto non lineare/elettromagnetico di sistemi wireless non convenzionali. Questo lavoro presenta un metodo rigoroso per considerare le interazioni tra due sistemi posti sia in condizioni di campo vicino che in condizioni di campo lontano. In sostanza, gli effetti del sistema trasmittente sono rappresentati da un generatore equivalente di Norton posto in parallelo all’antenna del sistema ricevente, calcolato per mezzo del teorema di reciprocità e del teorema di equivalenza. La correttezza del metodo è stata verificata per mezzo di simulazioni e misure, concordi tra loro. La stessa teoria, ampliata con l’introduzione degli effetti di scattering, è stata usata per valutare una condizione analoga, dove l’elemento trasmittente coincide con quello ricevente (DIE) contenuto all’interno di una struttura metallica (package). I risultati sono stati confrontati con i medesimi ottenibili tramite tecniche FEM e FDTD/FIT, che richiedono tempi di simulazione maggiori di un ordine di grandezza. Grazie ai metodi di co-simulazione non lineari/EM sopra esposti, è stato progettato e verificato un sistema di localizzazione e identificazione di oggetti taggati posti in ambiente indoor. Questo è stato ottenuto dotando il sistema di lettura, denominato RID (Remotely Identify and Detect), di funzioni di scansione angolare e della tecnica di RADAR mono-pulse. Il sistema sperimentale, creato con dispositivi low cost, opera a 2.5 GHz ed ha le dimensioni paragonabili ad un normale PDA. E’ stato sperimentata la capacità del RID di localizzare, in scenari indoor, oggetti statici e in movimento.

Ultra-low power WSNs: distributed signal processing and dynamic resource management

This thesis presents several data processing and compression techniques capable of addressing the strict requirements of wireless sensor networks. After introducing a general overview of sensor networks, the energy problem is introduced, dividing the different energy reduction approaches according to the different subsystem they try to optimize. To manage the complexity brought by these techniques, a quick overview of the most common middlewares for WSNs is given, describing in detail SPINE2, a framework for data processing in the node environment. The focus is then shifted on the in-network aggregation techniques, used to reduce data sent by the network nodes trying to prolong the network lifetime as long as possible. Among the several techniques, the most promising approach is the Compressive Sensing (CS). To investigate this technique, a practical implementation of the algorithm is compared against a simpler aggregation scheme, deriving a mixed algorithm able to successfully reduce the power consumption. The analysis moves from compression implemented on single nodes to CS for signal ensembles, trying to exploit the correlations among sensors and nodes to improve compression and reconstruction quality. The two main techniques for signal ensembles, Distributed CS (DCS) and Kronecker CS (KCS), are introduced and compared against a common set of data gathered by real deployments. The best trade-off between reconstruction quality and power consumption is then investigated. The usage of CS is also addressed when the signal of interest is sampled at a Sub-Nyquist rate, evaluating the reconstruction performance. Finally the group sparsity CS (GS-CS) is compared to another well-known technique for reconstruction of signals from an highly sub-sampled version. These two frameworks are compared again against a real data-set and an insightful analysis of the trade-off between reconstruction quality and lifetime is given.

Design, implementation and evaluation of a virtual laboratory for Computer Engineering Education

Broad consensus has been reached within the Education and Cognitive Psychology research communities on the need to center the learning process on experimentation and concrete application of knowledge, rather than on a bare transfer of notions. Several advantages arise from this educational approach, ranging from the reinforce of students learning, to the increased opportunity for a student to gain greater insight into the studied topics, up to the possibility for learners to acquire practical skills and long-lasting proficiency. This is especially true in Engineering education, where integrating conceptual knowledge and practical skills assumes a strategic importance. In this scenario, learners are called to play a primary role. They are actively involved in the construction of their own knowledge, instead of passively receiving it. As a result, traditional, teacher-centered learning environments should be replaced by novel learner-centered solutions. Information and Communication Technologies enable the development of innovative solutions that provide suitable answers to the need for the availability of experimentation supports in educational context. Virtual Laboratories, Adaptive Web-Based Educational Systems and Computer-Supported Collaborative Learning environments can significantly foster different learner-centered instructional strategies, offering the opportunity to enhance personalization, individualization and cooperation. More specifically, they allow students to explore different kinds of materials, to access and compare several information sources, to face real or realistic problems and to work on authentic and multi-facet case studies. In addition, they encourage cooperation among peers and provide support through coached and scaffolded activities aimed at fostering reflection and meta-cognitive reasoning. This dissertation will guide readers within this research field, presenting both the theoretical and applicative results of a research aimed at designing an open, flexible, learner-centered virtual lab for supporting students in learning Information Security.