Includes bibliographical references (p. 115-121).

Thesis (M.S. in computer engineering)--Washington State University, May 2009. / Title from PDF title page (viewed on Aug. 5, 2009). "School of Electrical Engineering and Computer Science." Includes bibliographical references (p. 29-31).

Thesis (PH.D.)--Michigan State University. Electrical Engineering, 2008. / Title from PDF t.p. (viewed on Aug. 11, 2009) Includes bibliographical references (p. 187-195). Also issued in print.

Thesis (M.E.)--University of Canterbury, 2008. / Typescript (photocopy). "April 2008." Includes bibliographical references (leaves [93]-96). Also available via the World Wide Web.

Thesis (M.S.)--Rochester Institute of Technology, 2009. / Typescript. Includes bibliographical references (leaves 54-56).

Thesis (M.S.)--Rochester Institute of Technology, 2007. / Typescript. Includes bibliographical references (leaves 97-98).

Στην διπλωματική εργασία γίνεται μια γενική μελέτη σχετικά με τα ασύρματα δίκτυα αισθητήρων τις εφαρμογές τους, της δομής των κόμβων, αναφορά στα δίκτυα, τις τοπολογίες και τα πρωτόκολλα που χρησιμοποιούνται στα συγκεκριμένα δίκτυα. Στην συνέχεια γίνεται μια αναφορά στο λειτουργικό σύστημα tinyOS και στη γλώσσα προγραμματισμού του nesC. Τέλος, στα πλαίσια της διπλωματικής εργασίας υλοποιήσαμε μια εφαρμογή που παρακολουθεί την υγρασία σε μια συγκεκριμένη περιοχή, χρησιμοποιώντας τα ασύρματα δίκτυα αισθητήρων και παρουσιάζει στον χρήστη τα αποτελέσματα με ένα γραφικό τρόπο. / The present thesis studies wireless sensor networks (WSN), on their applications, their structure, and reports on networks, topologies and their protocols used in WSN. Additionally a study on the tinyOS operating system using the programming language nesC is reported. In order to demonstrate the efficiency of WSN an application that monitors the humidity in a given area using wireless sensor network technology and the results are presented to the user in a graphic way

Η παρούσα διπλωματική εργασία πραγματεύεται την παρουσίαση των ασύρματων δικτύων αισθητήρων και ελεγκτών στην βιομηχανία. Η εργασία αυτή εκπονήθηκε στο Εργαστήριο Γενικής Ηλεκτροτεχνίας του Τμήματος Ηλεκτρολόγων Μηχανικών και Τεχνολογίας Υπολογιστών της Πολυτεχνικής Σχολής του Πανεπιστημίου Πατρών. Σκοπός είναι η δημιουργία μίας ολοκληρωμένης παρουσίασης για την τεχνολογία ασύρματης δικτύωσης σε βιομηχανικό περιβάλλον, ώστε να μπορεί ο αναγνώστης να κατανοήσει εις βάθος τα πλεονεκτήματα αλλά και τους κινδύνους από την εφαρμογή της, να ενημερωθεί σε ποιο επίπεδο εφαρμογής βρίσκεται σήμερα, καθώς και να κατανοήσει το τεχνικό μέρος της τεχνολογίας αυτής. Αρχικά έγινε μία εισαγωγή στο πώς δουλεύει η ασύρματη τεχνολογία και των βασικών χαρακτηριστικών της, (κεραίες τοπολογίες κλπ), ενώ παρουσιάστηκαν και τα διάφορα πρωτόκολλα που χρησιμοποιούνται στα ασύρματα δίκτυα γενικά. Στη συνέχεια έγινε παρουσίαση των απαιτήσεων για βιομηχανική δικτύωση (π.χ. ασφάλεια, αξιοπιστία) ενώ μελετήθηκε πώς μπορεί να γίνει στην πράξη η εφαρμογή των ασυρμάτων δικτύων στον τομέα της βιομηχανίας, δηλαδή τα πρωτόκολλα που χρησιμοποιούνται, καθώς και ανάλυση του τομέα της ασφάλειας δεδομένων κατά την ασύρματη μετάδοση στο βιομηχανικό περιβάλλον. Το επόμενο βήμα έγινε παρουσίαση του λογισμικού Prosoft Wireless Designer της εταιρίας Prosoft για τον σχεδιασμό βιομηχανικών δικτύων σε περιβάλλον υπολογιστή. Τέλος παρουσιάστηκαν επιλεκτικά παραδείγματα υλοποιημένων εφαρμογών ασύρματης δικτύωσης από εταιρίες, καθώς και διάφορα προϊόντα που κυκλοφορούν στην αγορά και χρησιμοποιούνται αποκλειστικά για βιομηχανική ασύρματη δικτύωση. / -

High information quality is a paramount requirement for wireless sensor network monitoring applications. However, it is challenging to achieve a cost effective information quality solution due to unpredictable environment noise and events, unreliable wireless channel and network bandwidth, and resource and energy constraints. Specifically, the dynamic and unreliable nature of WSNs make it difficult to pre-determine optimum sensor rates and predict packet loss. To address this problem, we use information quality metrics presented by [26, 11] which characterize information quality based on the sampling frequency of sensor nodes and the packet loss rate during network transmission. These fundamental quality metrics are based on signal-to-noise ratio and are therefore application independent. Based on these metrics, a quality-aware scheduling system (QSS) is developed, which exploits cross-layer control of sensor nodes to effectively schedule data sensing and forwarding. Particularly, we develop and evaluate several QSS scheduling mechanisms: passive, reactive and perceptive. These mechanisms can adapt to environment noise, bandwidth variation and wireless channel collisions by dynamically controlling sensor rates and sensor phase. Our software and hardware experimental results indicate that our QSS is a novel and effective approach to improve information quality for WSNs.

As redes de sensores sem fio (RSSF) são uma tecnologia que ganhou muita importância nos últimos anos. Dentro das diversas aplicações para essas redes, o rastreamento de alvos é considerado essencial. Nessa aplicação, a RSSF deve determinar, de forma colaborativa, a trajetória de um ou mais alvos que se encontrem dentro de sua área de cobertura. O presente trabalho apresenta um algoritmo colaborativo baseado na fatoração multifrontal QR para estimação de trajetórias de alvos com RSSF. A solução proposta está inserida no âmbito da estimação por lotes, na qual os dados são coletados pelos sensores durante a aplicação e só no final é realizada a estimativa da trajetória do alvo. Uma vez coletados os dados, o problema pode ser modelado como um sistema de equações sobredeterminado Ax = b cuja característica principal é ser esparso. A solução desse sistema é dada mediante o método de mínimos quadrados, no qual o sistema é transformado num sistema triangular superior, que é solucionado mediante substituição inversa. A fatoração multifrontal QR é ideal neste contexto devido à natureza esparsa da matriz principal do sistema. A fatoração multifrontal QR utiliza um grafo denominado árvore de eliminação para dividir o processo de fatoração de uma matriz esparsa em fatorações densas de pequenas submatrizes denominadas matrizes frontais. Mapeando a árvore de eliminação na RSSF consegue-se que essas fatorações densas sejam executadas pelos nós sensoriais que detectaram o alvo durante seu trajeto pela rede. Dessa maneira, o algoritmo consegue realizar a fatoração da matriz principal do problema de forma colaborativa, dividindo essa tarefa em pequenas tarefas que os nós de sensoriais da rede possam realizar. / Wireless Sensor Networks (WSN) is a technology that have gained a lot of importance in the last few years. From all the possible applications for WSN, target tracking is considered essential. In this application, the WSN has to determine, in a collaborative way, the trajectory of one or more targets that are within the sensing area of the network. The aim of this document is to present a collaborative algorithm based on multifrontal QR factorization for the solution of the target trajectory estimation problem with WSN. This algorithm uses a batch estimation approach, which assumes that all sensing data are available before the estimation of the target trajectory. If all the observations of the target trajectory is available, the problem can be modeled as an overdetermined system of equations Ax = b where A is sparse. This system of equations is solved by least squares method. The multifrontal QR factorization uses a tree graph called elimination tree to reorganize the overall factorization of a sparse matrix into a sequence of partial factorizations of dense smaller matrices named frontal matrices. By mapping the elimination tree into the WSN, the sensor nodes that observed the target can factorize the frontal matrices. In this manner, the WSN factorizes the matrix A in a collaborative way, dividing the work in small tasks that the sensor nodes could execute.