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.

Orientador: Eleri Cardozo, Eliane Gomes Guimarães / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-18T21:30:30Z (GMT). No. of bitstreams: 1 Souza_RicardodaSilva_M.pdf: 11513792 bytes, checksum: e5bbe5cf019713b9f5ce0673946aa7f2 (MD5) Previous issue date: 2011 / Resumo: Com a evolução da robótica móvel, é cada vez mais frequente soluções que buscam realizar o controle de robôs de forma distribuída. Este tipo de controle requer a existência de redes de comunicação sem fio conectando o robô a outros dispositivos no ambiente. Tecnologias como Wi-Fi e Bluetooth são exemplos de redes utilizadas para este fim. Redes Ad-hoc, como redes de sensores sem fio, podem ser rapidamente instaladas em um ambiente oferecendo cobertura em uma ampla região utilizando um grande número de nós. Além de prover comunicação para os robôs, uma rede de sensores pode também auxiliar na sua navegação, localização e ainda aumentar sua capacidade de sensoriamento. Esta dissertação apresenta uma plataforma que permite a integração de redes de sensores em aplicações de robótica móvel. Com esta integração é possível realizar o controle e a comunicação com robôs móveis por meio de redes de sensores sem fio / Abstract: A trend in today's mobile robotics is to perform the control of mobile robots in a distributed fashion. This control scheme requires a wireless communication network connecting the robot to the other existing devices in the environment. WiFi and Bluetooth are examples of such networks. Ad-hoc networks such as wireless sensor networks (WSN) can be deployed instantly and offer a wide coverage by employing a large number of communicating nodes. In addition to provide a communication link to the robots, a WSN can aid the robot's navigation, localization, and also enhance its sensory capabilities. This dissertation presents a platform that allows the integration of WSNs into mobile robotics applications. With this integration it is possible to control and communicate mobile robots through WSNs / Mestrado / Engenharia de Computação / Mestre em Engenharia Elétrica

Abstract Wireless sensor networks (WSNs) offer us a potential for greater awareness of our surroundings, collecting, measuring, and aggregating parameters beyond our current abilities, and provide an opportunity to enrich our experience through context-awareness. As a typical sensor node is small with limited processing power, memory, and energy resources, in particular, these WSNs must be very energy-efficient for practical deployment. Medium access control (MAC) protocols are central to the energy-efficiency objective of WSNs, as they directly control the most energy consuming part of a sensor node: communications over the shared medium. This thesis focuses on evaluating MAC protocols within the WSN domain by, firstly, surveying a representative number of MAC protocols and their features. Secondly, three novel MAC protocols are proposed, one for layered contention-based access, one for layered scheduled access, and one for cross-layer contention-based access. Thirdly, a novel energy consumption model is proposed, and fourthly, a holistic MAC protocol evaluation model is proposed that takes into account application emphasis on performance metrics. The MAC protocols are evaluated analytically. In addition, the layered contention-based MAC protocol has been implemented and measured, and the cross-layer contention-based protocol operating over an impulse radio-ultra wideband (IR-UWB) physical layer has been verified by simulations with relevant physical layer characteristics. The energy consumption evaluation model proposed is straightforward to modify for evaluating delay, and it can reuse state transition probabilities derived from throughput analysis. The holistic application-driven MAC protocol evaluation model uses a novel single compound metric that represents a MAC protocol's relative performance in a given application scenario. The evaluations have revealed several significant flaws in sensor MAC protocols that are adapted to sensor networking from ad hoc networks. Furthermore, it has been shown that, when taking sufficient details into account, single hop communications can outperform multi-hop communications in the energy perspective within the feasible transmission ranges provided by sensor nodes. The impulse radio physical layer introduces characteristics to MAC protocols that invalidate traditional techniques which model the physical layer in terms of simple collisions. Hence, these physical layer characteristics have been modelled and included in the analysis, which improves the level of agreements with simulated results.

Cognitive radio improves radio spectrum utilization either by spectrum sharing or by opportunistically utilizing the spectrum of the licensed users. Cognitive beam- forming is a prominent technique that can further enhance the overall performance of the wireless communication systems through beamforming vector design and/or power allocation. Harvesting radio frequency (RF) energy from existing wireless communication systems is a promising potential solution for providing convenient, perpetual and green energy supply to wireless sensor networks (WSN). The amount of energy that can be harvested from existing RF energy sources over a short period of time can only support low data rate applications with simply transmission strategies. The main challenge for satisfying the energy requirement of WSN is the time-varying wireless fading channels. Low complexity cooperation between WSN and RF energy source can effectively enhance the stability of energy supply for the sensor node. While multiple transmission antennas are deployed at the existing RF energy source, judicious transmit beam selection can further improve the harvested energy at the sensor node, while simultaneously serving multiple users. In this doctoral research, we present random unitary beamforming (RUB) cooperative beam selection schemes to ensure the QoS of primary system and reduce the hardware and software complexities of secondary system. We analyze the exact out- age performance of the primary system, and investigate the tradeoff between primary system outage probability versus secondary system sum-rate performance. We also study the performance of overlaid wireless sensor transmission powered by RF energy harvested from existing wireless system. We derive the exact distribution function of harvested energy over a certain number channel coherence time over Rayleigh fading channels with the consideration of hardware limitation, such as energy harvesting sensitivity and harvesting efficiency. We also analyze the average packet delay and packet loss probability of sensor transmission subject to interference from existing system, for both delay insensitive traffics and delay sensitive traffics. The optimal design of energy storage capacity of the sensor nodes is proposed to minimize the average packet transmission delay for delay insensitive traffics with two candidate transmission strategies. We further investigate the energy harvesting performance of a wireless sensor node powered by RF energy from an existing multiuser MIMO system. Specifically, we propose based cooperative beam selection schemes to enhance the energy harvesting performance at the sensor. We derive the exact distribution function of harvested energy in a coherence time and further investigate the performance tradeoff of the average harvested energy at the sensor versus the sum-rate of the multiuser MIMO system. / Graduate

Master of Science / Department of Computing and Information Sciences / Gurdip Singh / Wireless sensor networks are characterized by severe energy constraints, one to many flows and low rate redundant data. Most of the routing algorithms for traditional networks are address centric, and the ad hoc nature of wireless sensor network makes them unsuitable for practical applications. Also the algorithms designed for mobile ad hoc networks are unsuitable for wireless sensor networks due to severe energy constraints that require nodes to perform for months with limited resources, as well as the low data rate which the constraint implies. This thesis examines a model driven data gathering algorithm framework for wireless sensor networks. It was designed with a goal to decrease the overall cost in transmission by lowering the number of messages transmitted in the network. A combination of data- centric and address-centric approaches was used as guidelines during the design process. A shortest path heuristic where intermediate nodes forward interest messages whenever it is of lower cost is one of the heuristics used. Another heuristic used is the greedy incremental approach to build a lower cost tree from a graph with various producers and consumers. A cost division heuristic is used to divide cost of shared path into distinct paths as the path forks in a tree. This thesis analyzes the effects of these heuristics on the performance of the algorithm and how it lowers the overall cost with the addition of each heuristic.

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Sensor network web services have recently emerged as promising tools to provide remote management, data collection and querying capabilities for sensor networks. They can be utilized in a large number of elds among which Demand-Side Energy Management (DSEM) is an important application area that has become possible with the smart electrical power grid. DSEM applications generally aim to reduce the cost and the amount of power consumption. In the traditional power grid, DSEM has not been implemented widely due to the large number of households and lack of ne-grained automation tools. However by employing intelligent devices and implementing communication infrastructure among these devices, the smart grid will renovate the existing power grid and it will enable a wide variety of DSEM applications. In this thesis, we analyze various DSEM scenarios that become available with sensor network web services. We assume a smart home with a Wireless Sensor Network (WSN) where the sensors are mounted on the appliances and they are able to run web services. The web server retrieves data from the appliances via the web services running on the sensor nodes. These data can be stored in a database after processing, where the database can be accessed by the utility, as well as the inhabitants of the smart home. We showthat our implementation is e cient in terms of running time. Moreover, the message sizes and the implementation code is quite small which makes it suitable for the memory-limited sensor nodes. Furthermore, we show the application scenarios introduced in the thesis provide energy saving for the smart home.