Wireless sensor networks (WSNs) can provide new methods for information gathering for a variety of applications. In order to ensure the network quality of service, the quality of the measurements has to be guaranteed. Distributed fault detection and isolation schemes are preferred to centralized solutions to diagnose faulty sensors in WSNs. Indeed the first approach avoids the need for a central node that collects information from every sensor node, and hence it limits complexity and energy cost while improving reliability.In the case of state estimation over distributed architectures, the sensor faults can be propagated in the network during the information exchanging process. To build a reliable state estimate one has to make sure that the measurements issued by the different sensors are fault free. That is one of the motivations to build a distributed fault detection and isolation (FDI) system that generates an alarm as soon as a measurement is subject to a fault (has drift, cdots ). In order to diagnose faults with small magnitude in wireless sensor networks, a systematic methodology to design and implement a distributed FDI system is proposed. It resorts to distinguishability measures to indicate the performance of the FDI system and to select the most suitable node(s) for information exchange in the network with a view to FDI. It allows one to determine the minimum amount of data to be exchanged between the different nodes for a given FDI performance. In this way, the specifications for FDI can be achieved while the communication and computation cost are kept as small as possible. The distributed FDI systems are designed both in deterministic and stochastic frameworks. They are based on the parity space approach that exploits spacial redundancy as well as temporal redundancy in the context of distributed schemes. The decision systems with the deterministic method and the stochastic method are designed not only to detect a fault but also to distinguish which fault is occurring in the network. A case study with a WSN is conducted to verify the proposed method. The network is used to monitor the temperature and humidity in a computer room. The distributed FDI system is validated both with simulated data and recorded data. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

International Telemetering Conference Proceedings / October 27-30, 1997 / Riviera Hotel and Convention Center, Las Vegas, Nevada / There is a wave of change coming. It started in the industrial automation community and it is slowly and surely working its way into aerospace, satellite and telemetry applications. It’s called the PC, and its not just for simple quick-look data anymore. Using state-of-the-art commercial hardware and software technologies, PC-based architectures can now be used to perform self contained, reliable and high performance telemetry data acquisition and processing functions – previously the domain of expensive, dedicated front end systems. This paper will discuss many of the key enabling technologies and will provide examples of their use in a truly next generation system architecture based on the Microsoft® Windows NT Operating System and related features.

Through the work of researchers and the development of commercially availableproducts, automated guidance has become a viable option for agricultural producers.Some of the limitations of commercially available technologies are that they onlyautomate one function of the agricultural vehicle and that the systems are proprietary toa single machine model.The objective of this project was to evaluate a controller area network (CAN bus)as the basis of an automated guidance system. The prototype system utilized severalmicrocontroller-driven nodes to act as control points along a system wide CAN bus.Messages were transferred to the steering, transmission, and hitch control nodes from atask computer. The task computer utilized global positioning system data to determinethe appropriate control commands.Infield testing demonstrated that each of the control nodes could be controlledsimultaneously over the CAN bus. Results showed that the task computer adequatelyapplied a feedback control model to the system and achieved guidance accuracy levelswell within the range sought. Testing also demonstrated the system's ability tocomplete normal field operations such as headland turning and implement control.

The architecture of certain class of services, such as distributed computing, distributed storages or content delivering networks shifts from the traditional client-server model to more scalable and robust peer to peer networks. Providing proper protection to such complex, open and anonymous systems is very complicated. Malicious peers can cooperate and develop sophisticated strategies to bypass existing security mechanisms. Recently, many trust management systems for P2P networks have been proposed. However, their effectiveness is usually tested only against simple malicious strategies. Moreover, a complex comparison of resistance of a particular method is missing. In this thesis, we (1) propose a new trust management system called BubbleTrust and (2) develop a simulation framework for testing trust management systems against various malicious strategies. Our simulation framework defines several criteria which determine the success of each malicious strategy in the network with a given system. We present results of four trust management systems that represent main contemporary approaches and BubbleTrust.

Wireless sensor networks (WSNs) allow us to instrument the physical world in novel ways, providing detailed insight that has not been possible hitherto. Since WSNs provide an interface to the physical world, each sensor node has a location in physical space, thereby enabling us to associate spatial properties with data. Since WSNs can perform periodic sensing tasks, we can also associate temporal markers with data. In the environmental sciences, in particular, WSNs are on the way to becoming an important tool for the modelling of spatially and temporally extended physical phenomena. However, support for high-level and expressive spatial-analytic tasks that can be executed inside WSNs is still incipient. By spatial analysis we mean the ability to explore relationships between spatially-referenced entities (e.g., a vineyard, or a weather front) and to derive representations grounded on such relationships (e.g., the geometrical extent of that part of a vineyard that is covered by mist as the intersection of the geometries that characterize the vineyard and the weather front, respectively). The motivation for this endeavour stems primarily from applications where important decisions hinge on the detection of an event of interest (e.g., the presence, and spatio-temporal progression, of mist over a cultivated field may trigger a particular action) that can be characterized by an event-defining predicate (e.g., humidity greater than 98 and temperature less than 10). At present, in-network spatial analysis in WSN is not catered for by a comprehensive, expressive, well-founded framework. While there has been work on WSN event boundary detection and, in particular, on detecting topological change of WSN-represented spatial entities, this work has tended to be comparatively narrow in scope and aims. The contributions made in this research are constrained to WSNs where every node is tethered to one location in physical space. The research contributions reported here include (a) the definition of a framework for representing geometries; (b) the detailed characterization of an algebra of spatial operators closely inspired, in its scope and structure, by the Schneider-Guting ROSE algebra (i.e., one that is based on a discrete underlying geometry) over the geometries representable by the framework above; (c) distributed in-network algorithms for the operations in the spatial algebra over the representable geometries, thereby enabling (i) new geometries to be derived from induced and asserted ones, and (ii)topological relationships between geometries to be identified; (d) an algorithmic strategy for the evaluation of complex algebraic expressions that is divided into logically-cohesive components; (e) the development of a task processing system that each node is equipped with, thereby with allowing users to evaluate tasks on nodes; and (f) an empirical performance study of the resulting system.

Betrieb eines Knotens in einem Distributed Semantic Social Network. Der Knoten umfasst Funktionen zur Erstellung einer persönlichen Beschreibung, zur Verwaltung von Freundschaftsbeziehungen und zur Kommunikation mit anderen Teilnehmern des Netzwerks. Die entstandene Implementierung ist bereits auf leistungsschwacher, kostengünstiger und energieeffizienter Hardware praktisch im Einsatz. Zusätzlich wurden ihre Skalierungseigenschaften in einem Testaufbau mit mehreren Knoten untersucht.

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Considerando a importÃncia do controle da coagulaÃÃo quÃmica para o processo de tratamento de Ãgua por filtraÃÃo rÃpida, esta dissertaÃÃo propÃe a aplicaÃÃo de redes neurais artificiais para inferÃncia dos sinais de controle de dosagem de coagulantes principal e auxiliar, no processo de coagulaÃÃo quÃmica em uma estaÃÃo de tratamento de Ãgua por filtraÃÃo rÃpida. Para tanto, foi feito uma anÃlise comparativa da aplicaÃÃo de modelos baseados em redes neurais do tipo: alimentada adiante focada atrasada no tempo (FTLFN); alimentada adiante atrasada no tempo distribuÃda (DTLFN); recorrente de Elman (ERN) e auto-regressiva nÃo-linear com entradas exÃgenas (NARX). Da anÃlise comparativa, o modelo baseado em redes NARX apresentou melhores resultados, evidenciando o potencial do modelo para uso em casos reais, o que contribuirà para a viabilizaÃÃo de projetos desta natureza em estaÃÃes de tratamento de Ãgua de pequeno porte. / Considering the importance of the chemical coagulation control for the water treatment by direct filtration, this work proposes the application of artificial neural networks for inference of dosage control signals of principal and auxiliary coagulant, in the chemical coagulation process in a water treatment plant by direct filtration. To that end, was made a comparative analysis of the application of models based on neural networks, such as: Focused Time Lagged Feedforward Network (FTLFN); Distributed Time Lagged Feedforward Network (DTLFN); Elman Recurrent Network (ERN) and Non-linear Autoregressive with exogenous inputs (NARX). From the comparative analysis, the model based on NARX networks showed better results, demonstrating the potential of the model for use in real cases, which will contribute to the viability of projects of this nature in small size water treatment plants.