Resilient Wireless Sensor Networks Using Topology Control: A Review

Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs.

Multiple feature points representation in target localization of wireless visual sensor networks

This paper discusses the target localization problem in wireless visual sensor networks. Additive noises and measurement errors will affect the accuracy of target localization when the visual nodes are equipped with low-resolution cameras. In the goal of improving the accuracy of target localization without prior knowledge of the target, each node extracts multiple feature points from images to represent the target at the sensor node level. A statistical method is presented to match the most correlated feature point pair for merging the position information of different sensor nodes at the base station. Besides, in the case that more than one target exists in the field of interest, a scheme for locating multiple targets is provided. Simulation results show that, our proposed method has desirable performance in improving the accuracy of locating single target or multiple targets. Results also show that the proposed method has a better trade-off between camera node usage and localization accuracy.

A set of canonical problems in sloshing. Part 0: Experimental setup and data processing

In a series of attempts to research and document relevant sloshing type phenomena, a series of experiments have been conducted. The aim of this paper is to describe the setup and data processing of such experiments. A sloshing tank is subjected to angular motion. As a result pressure registers are obtained at several locations, together with the motion data, torque and a collection of image and video information. The experimental rig and the data acquisition systems are described. Useful information for experimental sloshing research practitioners is provided. This information is related to the liquids used in the experiments, the dying techniques, tank building processes, synchronization of acquisition systems, etc. A new procedure for reconstructing experimental data, that takes into account experimental uncertainties, is presented. This procedure is based on a least squares spline approximation of the data. Based on a deterministic approach to the first sloshing wave impact event in a sloshing experiment, an uncertainty analysis procedure of the associated first pressure peak value is described.

Generating multimedia presentations that summarize the behavior of dynamic systems using a model-based approach

This article describes a knowledge-based method for generating multimedia descriptions that summarize the behavior of dynamic systems. We designed this method for users who monitor the behavior of a dynamic system with the help of sensor networks and make decisions according to prefixed management goals. Our method generates presentations using different modes such as text in natural language, 2D graphics and 3D animations. The method uses a qualitative representation of the dynamic system based on hierarchies of components and causal influences. The method includes an abstraction generator that uses the system representation to find and aggregate relevant data at an appropriate level of abstraction. In addition, the method includes a hierarchical planner to generate a presentation using a model with dis- course patterns. Our method provides an efficient and flexible solution to generate concise and adapted multimedia presentations that summarize thousands of time series. It is general to be adapted to differ- ent dynamic systems with acceptable knowledge acquisition effort by reusing and adapting intuitive rep- resentations. We validated our method and evaluated its practical utility by developing several models for an application that worked in continuous real time operation for more than 1 year, summarizing sen- sor data of a national hydrologic information system in Spain.

Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Artificial Neural Networks still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning ANN parameters. In recent years the use of hybrid technologies, combining Artificial Neural Networks and Genetic Algorithms, has been utilized to. In this work, several ANN topologies were trained and tested using Artificial Neural Networks and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out.

Cooperation between expert knowledge and data mining discovered knowledge: Lessons learned

Expert systems are built from knowledge traditionally elicited from the human expert. It is precisely knowledge elicitation from the expert that is the bottleneck in expert system construction. On the other hand, a data mining system, which automatically extracts knowledge, needs expert guidance on the successive decisions to be made in each of the system phases. In this context, expert knowledge and data mining discovered knowledge can cooperate, maximizing their individual capabilities: data mining discovered knowledge can be used as a complementary source of knowledge for the expert system, whereas expert knowledge can be used to guide the data mining process. This article summarizes different examples of systems where there is cooperation between expert knowledge and data mining discovered knowledge and reports our experience of such cooperation gathered from a medical diagnosis project called Intelligent Interpretation of Isokinetics Data, which we developed. From that experience, a series of lessons were learned throughout project development. Some of these lessons are generally applicable and others pertain exclusively to certain project types.

Secure neighbor discovery in wireless sensor networks using range-free localization techniques

Si una red inalámbrica de sensores se implementa en un entorno hostil, las limitaciones intrínsecas a los nodos conllevan muchos problemas de seguridad. En este artículo se aborda un ataque particular a los protocolos de localización y descubrimiento de vecinos, llevada a cabo por dos nodos que actúan en connivencia y establecen un "agujero de gusano" para tratar de engañar a un nodo aislado, haciéndole creer que se encuentra en la vecindad de un conjunto de nodos locales. Para contrarrestar este tipo de amenazas, se presenta un marco de actuación genéricamente denominado "detection of wormhole attacks using range-free methods" (DWARF) dentro del cual derivamos dos estrategias para de detección de agujeros de gusano: el primer enfoque (DWARFLoc) realiza conjuntamente la localización y la detección de ataques, mientras que el otro (DWARFTest) valida la posición estimada por el nodo una vez finalizado el protocolo de localización. Las simulaciones muestran que ambas estrategias son eficaces en la detección de ataques tipo "agujero de gusano", y sus prestaciones se comparan con las de un test convencional basado en la razón de verosimilitudes.

Optimal design of AC EMI filters with damping networks and effect on the systems power factor

The cutoff frequencies of an EMI filter are normally given by the noise attenuation requirements the filter has to fulfill. In order to select the component values of the filter elements, i.e. inductances and capacitances, an additional design criterium is needed. In this paper the effect of the EMI filter input and output impedances are considered. The input impedance influences the filters effect on the system displacement power factor and the output impedance plays a key role in the system stability. The effect of filter element values, the number of filter stages as well as additional damping networks are considered and a design procedure is provided. For this analysis a two-port description of the input filters employing ABCD-parameters is used.

Simulador WKM para gestión de conocimiento en una WSN

La gestión del conocimiento (KM) se basa en la captación, filtración, procesamiento y análisis de unos datos en bruto que con dicho refinamiento podrán llegar a convertirse en conocimiento o Sabiduría. Estas prácticas tendrán lugar en este PFC en una WSN (Wireless Sensor Network) compuesta de unos sofisticados dispositivos comúnmente conocidos como “motas” y cuya principal característica son sus bajas capacidades en cuanto a memoria, batería o autonomía. Ha sido objetivo primordial de este Proyecto de fin de Carrera aunar una WSN con la Gestión del Conocimiento así como demostrar que es posible llevar a cabo grandes procesamientos de información, con tan bajas capacidades, si se distribuyen correctamente los procesos. En primera instancia, se introducen conceptos básicos acerca de las WSN (Wireless Sensor Networks) así como de los elementos principales en dichas redes. Tras conocer el modelo de arquitectura de comunicaciones se procede a presentar la Gestión del Conocimiento de forma teórica y a continuación la interpretación que se ha hecho a partir de diversas referencias bibliográficas para llevar a cabo la implementación del proyecto. El siguiente paso es describir punto por punto todos los componentes del Simulador; librerías, funcionamiento y demás cuestiones sobre configuración y puesta a punto. Como escenario de aplicación se plantea una red de sensores inalámbricos básica cuya topología y ubicación es completamente configurable. Se lleva a cabo una configuración a nivel de red basada en el protocolo 6LowPAN pero con posibilidad de simplificarlo. Los datos se procesan de acuerdo a un modelo piramidal de Gestión de Conocimiento adaptable a las necesidades del usuario. Mediante la utilización de las diversas opciones que proporciona la interfaz gráfica implementada y los documentos de resultados que se van generando, se puede llevar a cabo un detallado estudio posterior de la simulación y comprobar si se cumplen las expectativas planteadas. Knowledge management (KM) is based on the collection, filtering, processing and analysis of some raw data which such refinement it can be turned into knowledge or wisdom. These practices will take place in a WSN (Wireless Sensor Network) consists of sophisticated devices commonly known as "dots" and whose main characteristics are its low capacity for memory, battery or autonomy. A primary objective of this Project will be to join a WSN with Knowledge Management and show that it is possible make largo information processing, with such low capacity if the processes are properly distributed. First, we introduce basic concepts about the WSN (Wireless Sensor Networks) and major elements of these networks. After meeting the communications architecture model, we proceed to show the Knowledge Management theory and then the interpretation of several bibliographic references to carry out the project implementation. The next step is discovering point by point all over the Simulator components; libraries, operation and the rest of points about configuration and tuning. As application scenario we propose a basic wireless sensor network whose topology and location is completely customizable. It will perform a network level configuration based in W6LowPAN Protocol. Data is processed according to a pyramidal pattern Knowledge Management adaptable to the user´s needs. The hardware elements will suffer more or less energy dependence depending on their role and activity in the network. Through the various options that provide the graphical interface has been implemented and results documents that are generated, can be carried out after a detailed study of the simulation and verify compliance with the expectations raised.

Discussion of "Bibliography and Data on Cable-Stayed Bridges", by the Subcommittee on Cable-Stayed Bridges of the Committee on Long-Span Steel Bridges of the Committee on Metals of the Structural Division (Oct., 1977)

The writer would like to point out the existence of a very remarkable Spanish cable-stayed bridge built in 1925, wich is thus older than the first one recorded by the authors (and probably the pioneer in concrete-deck type). The Tempul Aqueduct was designed by the famous Professor Educardo Torroja. The deck is a concrete box girder sustained by two planes of 3 mm diam 37-wire double cables working at 27 kg/mm2.

Dental Implants Success Prediction: Tomography Based and Data Mining Based Approach.

There are a number of factors that contribute to the success of dental implant operations. Among others, is the choice of location in which the prosthetic tooth is to be implanted. This project offers a new approach to analyse jaw tissue for the purpose of selecting suitable locations for teeth implant operations. The application developed takes as input jaw computed tomography stack of slices and trims data outside the jaw area, which is the point of interest. It then reconstructs a three dimensional model of the jaw highlighting points of interest on the reconstructed model. On another hand, data mining techniques have been utilised in order to construct a prediction model based on an information dataset of previous dental implant operations with observed stability values. The goal is to find patterns within the dataset that would help predicting the success likelihood of an implant.

Structuring research methods and data with the research object model: genomics workflows as a case study

Background: One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e.g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows. Results: We present the application of the workflow-centric RO model for our bioinformatics case study. Three workflows were produced following recently defined Best Practices for workflow design. By modelling the experiment as an RO, we were able to automatically query the experiment and answer questions such as “which particular data was input to a particular workflow to test a particular hypothesis?”, and “which particular conclusions were drawn from a particular workflow?”. Conclusions: Applying a workflow-centric RO model to aggregate and annotate the resources used in a bioinformatics experiment, allowed us to retrieve the conclusions of the experiment in the context of the driving hypothesis, the executed workflows and their input data. The RO model is an extendable reference model that can be used by other systems as well.

The Imaging and Slitless Spectroscopy Instrument for Surveys (ISSIS): expected radiometric performance, operation modes and data handling

ISSIS is the instrument for imaging and slitless spectroscopy on-board WSO-UV. In this article, a detailed comparison between ISSIS expected radiometric performance and other ultraviolet instruments is shown. In addition, we present preliminary information on the performance verification tests and on the foreseen procedures for in-flight operation and data handling.

Aportación de la monitorización mediante redes de sensores y técnicas no invasivas para la conservación preventiva del Patrimonio

La presente tesis doctoral presenta una serie de estudios en el campo del patrimonio basados en metodologías de monitorización mediante redes de sensores y técnicas no invasivas con el objetivo de realizar nuevas aportaciones a la conservación preventiva mediante el seguimiento de los daños de deterioro o la prevención de los mismos. Las metodologías de monitorización mediante el despliegue de redes tridimensionales basadas en data loggers abordan estudios microclimáticos, de confort y energéticos a corto plazo, donde se establecen conclusiones relativas a la eficiencia energética de tres sistemas de calefacción muy utilizados en iglesias de la región centro de la Península Ibérica, abordando aspectos de afección de los mismos en el confort de los ocupantes o en el deterioro de los elementos patrimoniales o constructivos. Se desplegaron además distintas plataformas de redes de sensores inalámbricas procediendo a analizar en esta tesis cuál es la que presenta mejores resultados en el ámbito del patrimonio con el objetivo de una monitorización a largo plazo y considerando aspectos de comunicaciones, consumo y configuración de las redes. Una vez conocida la plataforma que presenta mejores resultados comparativos se muestra una metodología de estudio de la calidad de las comunicaciones en múltiples escenarios de patrimonio cultural y natural con la misma, que servirá para establecer una serie de aspectos a considerar en el despliegue de redes de sensores inalámbricas en futuros escenarios a monitorizar. Al igual que ocurre con las redes de sensores basadas en data loggers, las tareas de monitorización desarrolladas en esta tesis mediante el despliegue de las distintas plataformas inalámbricas ha permitido la detección de numerosos fenómenos de deterioro que son descritos a lo largo de la investigación y cuyo seguimiento supone una aportación a la prevención de daños en los distintos escenarios. Asimismo en el desarrollo de la tesis se realiza una aportación para la conservación preventiva mediante la monitorización con distintas técnicas no invasivas como la termografía infrarroja, las medidas de humedad superficial mediante protimeter, las técnicas de prospección de resistividad eléctrica de alta resolución o la prospección georradar. De este modo se desarrollan distintas aportaciones y conclusiones acerca de las ventajas y/o limitaciones de uso de las mismas analizando la idoneidad de aplicar cada una de ellas en distintas fases de análisis o con distintas capacidades de detección o caracterización de los daños. El estudio de imbricación de dichas técnicas ha sido desarrollado en un escenario real que presenta graves daños por humedad, habiendo sido posible la caracterización del origen de los mismos. ABSTRACT This doctoral dissertation discusses field research conducted to monitor heritage assets with sensor networks and other non-invasive techniques. The aim pursued was to contribute to conservation by tracking or preventing decay-induced damage. Monitoring methodologies based on three-dimensional data logger networks were used in short-term micro-climatic, comfort and energy studies to draw conclusions about the energy efficiency of three heating systems widely used in central Iberian churches. The impact of these systems on occupant comfort and decay of heritage or built elements was also explored. Different wireless sensor platforms were deployed and analysed to determine which delivered the best results in the context of long-term heritage monitoring from the standpoints of communications, energy demand and network architecture. A methodology was subsequently designed to study communication quality in a number of cultural and natural heritage scenarios and help establish the considerations to be borne in mind when deploying wireless sensor networks for heritage monitoring in future. As in data logger-based sensor networks, the monitoring conducted in this research with wireless platforms identified many instances of decay, described hereunder. Tracking those situations will help prevent damage in the respective scenarios. The research also contributes to preventive conservation based on non-invasive monitoring using techniques such as infrared thermography, protimeter-based surface damp measurements, high resolution electrical resistivity surveys and georadar analysis. The conclusions drawn address the advantages and drawbacks of each technique and its suitability for the various phases of analysis and capacity to detect or characterise damage. This dissertation also describes the intermeshed usage of these techniques that led to the identification of the origin of severe damp-induced damage in a real scenario.

How should the sustainability of the location of dry ports be measured? A proposed methodology using Bayesian networks and multi-criteria decision analysis

The global economic structure, with its decentralized production and the consequent increase in freight traffic all over the world, creates considerable problems and challenges for the freight transport sector. This situation has led shipping to become the most suitable and cheapest way to transport goods. Thus, ports are configured as nodes with critical importance in the logistics supply chain as a link between two transport systems, sea and land. Increase in activity at seaports is producing three undesirable effects: increasing road congestion, lack of open space in port installations and a significant environmental impact on seaports. These adverse effects can be mitigated by moving part of the activity inland. Implementation of dry ports is a possible solution and would also provide an opportunity to strengthen intermodal solutions as part of an integrated and more sustainable transport chain, acting as a link between road and railway networks. In this sense, implementation of dry ports allows the separation of the links of the transport chain, thus facilitating the shortest possible routes for the lowest capacity and most polluting means of transport. Thus, the decision of where to locate a dry port demands a thorough analysis of the whole logistics supply chain, with the objective of transferring the largest volume of goods possible from road to more energy efficient means of transport, like rail or short-sea shipping, that are less harmful to the environment. However, the decision of where to locate a dry port must also ensure the sustainability of the site. Thus, the main goal of this article is to research the variables influencing the sustainability of dry port location and how this sustainability can be evaluated. With this objective, in this paper we present a methodology for assessing the sustainability of locations by the use of Multi-Criteria Decision Analysis (MCDA) and Bayesian Networks (BNs). MCDA is used as a way to establish a scoring, whilst BNs were chosen to eliminate arbitrariness in setting the weightings using a technique that allows us to prioritize each variable according to the relationships established in the set of variables. In order to determine the relationships between all the variables involved in the decision, giving us the importance of each factor and variable, we built a K2 BN algorithm. To obtain the scores of each variable, we used a complete cartography analysed by ArcGIS. Recognising that setting the most appropriate location to place a dry port is a geographical multidisciplinary problem, with significant economic, social and environmental implications, we consider 41 variables (grouped into 17 factors) which respond to this need. As a case of study, the sustainability of all of the 10 existing dry ports in Spain has been evaluated. In this set of logistics platforms, we found that the most important variables for achieving sustainability are those related to environmental protection, so the sustainability of the locations requires a great respect for the natural environment and the urban environment in which they are framed.