28 resultados para wireless sensors


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Una red inalámbrica de sensores (Wireless Sensor Network, WSN) constituye un sistema de comunicación de datos flexible utilizado como alternativa a las redes cableadas o como extensión de éstas. Una de las aplicaciones de estas redes es para su uso en sistemas de predicción y prevención de incendios en áreas naturales. Su implementación se basa en el despliegue de sensores inalámbricos, realizado en una zona de riesgo de incendio que puedan recolectar información tal como temperatura, humedad y presión. Desde una estación base (o nodo "sumidero"), se suministra la información de los sensores a un centro de monitorización y control de forma estructurada. En estos centros la información recibida puede ser analizada, procesada y visualizada en tiempo real. Desde este centro de control se puede controlar también la red WSN modificando el comportamiento de los sensores según el nivel de riesgo de incendio detectado. Este proyecto se basa en el diseño, desarrollo e implementación de un Sistema de Control y Visualización de Información sobre Riesgo de Incendio (SCVIRI), que implementa las funciones de los centros de monitorización y control. La implementación de este sistema, junto con el desarrollado, en paralelo, de otro proyecto denominado Sistema de Estimación de Riesgo de Incendio Utilizando una WSN (SERIUW) que implementa la emulación de la red WSN, conforman un sistema general de anticipación y seguimiento de Fuegos. Se han realizado pruebas de funcionalidad y eficacia, incluidas en la presente memoria del sistema general (ambos proyectos), en un entorno controlado simulado. Este sistema es una solución para la lucha contra los incendios forestales ya que predice y previene, de forma temprana, posibles incendios en las áreas naturales bajo supervisión. Ante un evento de incendio declarado este sistema es un poderoso instrumento de apoyo permitiendo, por un lado, generar alertas automáticas (con localización y gravedad de fuegos detectados) y por el otro, hacer un seguimiento del incendio con mapas en tiempo real (con su consecuente apoyo para la protección e información con las brigadas de bomberos en las zonas activas). ABSTRACT. A wireless sensor network (WSN) is a flexible data communication system used as an alternative to wired networks or as an extension of them. One possible application of these networks is related to fire prediction and prevention in natural areas. Its implementation is based on a deployment of wireless sensors, in an area with high or moderate fire risk, to collect information such as temperature, humidity, luminance and pressure. A base station (or "sink") sends the collected information to a monitoring and control center according to an agreed structured format. At this center, the information received can be analyzed, processed and displayed in real time by using monitoring systems. From this control center the WSN can also be controlled by changing the sensors behavior in consistence with the detected level of fire risk. The work carried out in this project consists on the design, development and implementation of a system named SCVIRI, which implements the functions of the aforementioned monitoring and control center. This system works in connection with other one, called SERIUW, which has been developed in a different project and implements the WSN in an emulated environment. These two systems working together make up a general system of anticipation and monitoring of fires. This document also includes the functionality and performance tests performed on the overall system in a controlled and simulated environment. The global system is a solution that makes it easier to predict and prevent possible fires in natural areas under supervision. This system can be a powerful tool since, before a fire event is declared, it generates automatic alerts (including location and severity information) and allows the real-time motorization of fire evolution and its graphical visualization on maps. This could be also very useful for providing fire brigades with support, protection and information in zones in which a fire is already active.

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Las redes del futuro, incluyendo las redes de próxima generación, tienen entre sus objetivos de diseño el control sobre el consumo de energía y la conectividad de la red. Estos objetivos cobran especial relevancia cuando hablamos de redes con capacidades limitadas, como es el caso de las redes de sensores inalámbricos (WSN por sus siglas en inglés). Estas redes se caracterizan por estar formadas por dispositivos de baja o muy baja capacidad de proceso y por depender de baterías para su alimentación. Por tanto la optimización de la energía consumida se hace muy importante. Son muchas las propuestas que se han realizado para optimizar el consumo de energía en este tipo de redes. Quizás las más conocidas son las que se basan en la planificación coordinada de periodos de actividad e inactividad, siendo una de las formas más eficaces para extender el tiempo de vida de las baterías. La propuesta que se presenta en este trabajo se basa en el control de la conectividad mediante una aproximación probabilística. La idea subyacente es que se puede esperar que una red mantenga la conectividad si todos sus nodos tienen al menos un número determinado de vecinos. Empleando algún mecanismo que mantenga ese número, se espera que se pueda mantener la conectividad con un consumo energético menor que si se empleara una potencia de transmisión fija que garantizara una conectividad similar. Para que el mecanismo sea eficiente debe tener la menor huella posible en los dispositivos donde se vaya a emplear. Por eso se propone el uso de un sistema auto-adaptativo basado en control mediante lógica borrosa. En este trabajo se ha diseñado e implementado el sistema descrito, y se ha probado en un despliegue real confirmando que efectivamente existen configuraciones posibles que permiten mantener la conectividad ahorrando energía con respecto al uso de una potencia de transmisión fija. ABSTRACT. Among the design goals for future networks, including next generation networks, we can find the energy consumption and the connectivity. These two goals are of special relevance when dealing with constrained networks. That is the case of Wireless Sensors Networks (WSN). These networks consist of devices with low or very low processing capabilities. They also depend on batteries for their operation. Thus energy optimization becomes a very important issue. Several proposals have been made for optimizing the energy consumption in this kind of networks. Perhaps the best known are those based on the coordinated planning of active and sleep intervals. They are indeed one of the most effective ways to extend the lifetime of the batteries. The proposal presented in this work uses a probabilistic approach to control the connectivity of a network. The underlying idea is that it is highly probable that the network will have a good connectivity if all the nodes have a minimum number of neighbors. By using some mechanism to reach that number, we hope that we can preserve the connectivity with a lower energy consumption compared to the required one if a fixed transmission power is used to achieve a similar connectivity. The mechanism must have the smallest footprint possible on the devices being used in order to be efficient. Therefore a fuzzy control based self-adaptive system is proposed. This work includes the design and implementation of the described system. It also has been validated in a real scenario deployment. We have obtained results supporting that there exist configurations where it is possible to get a good connectivity saving energy when compared to the use of a fixed transmission power for a similar connectivity.

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El interés cada vez mayor por las redes de sensores inalámbricos pueden ser entendido simplemente pensando en lo que esencialmente son: un gran número de pequeños nodos sensores autoalimentados que recogen información o detectan eventos especiales y se comunican de manera inalámbrica, con el objetivo final de entregar sus datos procesados a una estación base. Los nodos sensores están densamente desplegados dentro del área de interés, se pueden desplegar al azar y tienen capacidad de cooperación. Por lo general, estos dispositivos son pequeños y de bajo costo, de modo que pueden ser producidos y desplegados en gran numero aunque sus recursos en términos de energía, memoria, velocidad de cálculo y ancho de banda están enormemente limitados. Detección, tratamiento y comunicación son tres elementos clave cuya combinación en un pequeño dispositivo permite lograr un gran número de aplicaciones. Las redes de sensores proporcionan oportunidades sin fin, pero al mismo tiempo plantean retos formidables, tales como lograr el máximo rendimiento de una energía que es escasa y por lo general un recurso no renovable. Sin embargo, los recientes avances en la integración a gran escala, integrado de hardware de computación, comunicaciones, y en general, la convergencia de la informática y las comunicaciones, están haciendo de esta tecnología emergente una realidad. Del mismo modo, los avances en la nanotecnología están empezando a hacer que todo gire entorno a las redes de pequeños sensores y actuadores distribuidos. Hay diferentes tipos de sensores tales como sensores de presión, acelerómetros, cámaras, sensores térmicos o un simple micrófono. Supervisan las condiciones presentes en diferentes lugares tales como la temperatura, humedad, el movimiento, la luminosidad, presión, composición del suelo, los niveles de ruido, la presencia o ausencia de ciertos tipos de objetos, los niveles de tensión mecánica sobre objetos adheridos y las características momentáneas tales como la velocidad , la dirección y el tamaño de un objeto, etc. Se comprobara el estado de las Redes Inalámbricas de Sensores y se revisaran los protocolos más famosos. Así mismo, se examinara la identificación por radiofrecuencia (RFID) ya que se está convirtiendo en algo actual y su presencia importante. La RFID tiene un papel crucial que desempeñar en el futuro en el mundo de los negocios y los individuos por igual. El impacto mundial que ha tenido la identificación sin cables está ejerciendo fuertes presiones en la tecnología RFID, los servicios de investigación y desarrollo, desarrollo de normas, el cumplimiento de la seguridad y la privacidad y muchos más. Su potencial económico se ha demostrado en algunos países mientras que otros están simplemente en etapas de planificación o en etapas piloto, pero aun tiene que afianzarse o desarrollarse a través de la modernización de los modelos de negocio y aplicaciones para poder tener un mayor impacto en la sociedad. Las posibles aplicaciones de redes de sensores son de interés para la mayoría de campos. La monitorización ambiental, la guerra, la educación infantil, la vigilancia, la micro-cirugía y la agricultura son solo unos pocos ejemplos de los muchísimos campos en los que tienen cabida las redes mencionadas anteriormente. Estados Unidos de América es probablemente el país que más ha investigado en esta área por lo que veremos muchas soluciones propuestas provenientes de ese país. Universidades como Berkeley, UCLA (Universidad de California, Los Ángeles) Harvard y empresas como Intel lideran dichas investigaciones. Pero no solo EE.UU. usa e investiga las redes de sensores inalámbricos. La Universidad de Southampton, por ejemplo, está desarrollando una tecnología para monitorear el comportamiento de los glaciares mediante redes de sensores que contribuyen a la investigación fundamental en glaciología y de las redes de sensores inalámbricos. Así mismo, Coalesenses GmbH (Alemania) y Zurich ETH están trabajando en diversas aplicaciones para redes de sensores inalámbricos en numerosas áreas. Una solución española será la elegida para ser examinada más a fondo por ser innovadora, adaptable y polivalente. Este estudio del sensor se ha centrado principalmente en aplicaciones de tráfico, pero no se puede olvidar la lista de más de 50 aplicaciones diferentes que ha sido publicada por la firma creadora de este sensor específico. En la actualidad hay muchas tecnologías de vigilancia de vehículos, incluidos los sensores de bucle, cámaras de video, sensores de imagen, sensores infrarrojos, radares de microondas, GPS, etc. El rendimiento es aceptable, pero no suficiente, debido a su limitada cobertura y caros costos de implementación y mantenimiento, especialmente este ultimo. Tienen defectos tales como: línea de visión, baja exactitud, dependen mucho del ambiente y del clima, no se puede realizar trabajos de mantenimiento sin interrumpir las mediciones, la noche puede condicionar muchos de ellos, tienen altos costos de instalación y mantenimiento, etc. Por consiguiente, en las aplicaciones reales de circulación, los datos recibidos son insuficientes o malos en términos de tiempo real debido al escaso número de detectores y su costo. Con el aumento de vehículos en las redes viales urbanas las tecnologías de detección de vehículos se enfrentan a nuevas exigencias. Las redes de sensores inalámbricos son actualmente una de las tecnologías más avanzadas y una revolución en la detección de información remota y en las aplicaciones de recogida. Las perspectivas de aplicación en el sistema inteligente de transporte son muy amplias. Con este fin se ha desarrollado un programa de localización de objetivos y recuento utilizando una red de sensores binarios. Esto permite que el sensor necesite mucha menos energía durante la transmisión de información y que los dispositivos sean más independientes con el fin de tener un mejor control de tráfico. La aplicación se centra en la eficacia de la colaboración de los sensores en el seguimiento más que en los protocolos de comunicación utilizados por los nodos sensores. Las operaciones de salida y retorno en las vacaciones son un buen ejemplo de por qué es necesario llevar la cuenta de los coches en las carreteras. Para ello se ha desarrollado una simulación en Matlab con el objetivo localizar objetivos y contarlos con una red de sensores binarios. Dicho programa se podría implementar en el sensor que Libelium, la empresa creadora del sensor que se examinara concienzudamente, ha desarrollado. Esto permitiría que el aparato necesitase mucha menos energía durante la transmisión de información y los dispositivos sean más independientes. Los prometedores resultados obtenidos indican que los sensores de proximidad binarios pueden formar la base de una arquitectura robusta para la vigilancia de áreas amplias y para el seguimiento de objetivos. Cuando el movimiento de dichos objetivos es suficientemente suave, no tiene cambios bruscos de trayectoria, el algoritmo ClusterTrack proporciona un rendimiento excelente en términos de identificación y seguimiento de trayectorias los objetos designados como blancos. Este algoritmo podría, por supuesto, ser utilizado para numerosas aplicaciones y se podría seguir esta línea de trabajo para futuras investigaciones. No es sorprendente que las redes de sensores de binarios de proximidad hayan atraído mucha atención últimamente ya que, a pesar de la información mínima de un sensor de proximidad binario proporciona, las redes de este tipo pueden realizar un seguimiento de todo tipo de objetivos con la precisión suficiente. Abstract The increasing interest in wireless sensor networks can be promptly understood simply by thinking about what they essentially are: a large number of small sensing self-powered nodes which gather information or detect special events and communicate in a wireless fashion, with the end goal of handing their processed data to a base station. The sensor nodes are densely deployed inside the phenomenon, they deploy random and have cooperative capabilities. Usually these devices are small and inexpensive, so that they can be produced and deployed in large numbers, and so their resources in terms of energy, memory, computational speed and bandwidth are severely constrained. Sensing, processing and communication are three key elements whose combination in one tiny device gives rise to a vast number of applications. Sensor networks provide endless opportunities, but at the same time pose formidable challenges, such as the fact that energy is a scarce and usually non-renewable resource. However, recent advances in low power Very Large Scale Integration, embedded computing, communication hardware, and in general, the convergence of computing and communications, are making this emerging technology a reality. Likewise, advances in nanotechnology and Micro Electro-Mechanical Systems are pushing toward networks of tiny distributed sensors and actuators. There are different sensors such as pressure, accelerometer, camera, thermal, and microphone. They monitor conditions at different locations, such as temperature, humidity, vehicular movement, lightning condition, pressure, soil makeup, noise levels, the presence or absence of certain kinds of objects, mechanical stress levels on attached objects, the current characteristics such as speed, direction and size of an object, etc. The state of Wireless Sensor Networks will be checked and the most famous protocols reviewed. As Radio Frequency Identification (RFID) is becoming extremely present and important nowadays, it will be examined as well. RFID has a crucial role to play in business and for individuals alike going forward. The impact of ‘wireless’ identification is exerting strong pressures in RFID technology and services research and development, standards development, security compliance and privacy, and many more. The economic value is proven in some countries while others are just on the verge of planning or in pilot stages, but the wider spread of usage has yet to take hold or unfold through the modernisation of business models and applications. Possible applications of sensor networks are of interest to the most diverse fields. Environmental monitoring, warfare, child education, surveillance, micro-surgery, and agriculture are only a few examples. Some real hardware applications in the United States of America will be checked as it is probably the country that has investigated most in this area. Universities like Berkeley, UCLA (University of California, Los Angeles) Harvard and enterprises such as Intel are leading those investigations. But not just USA has been using and investigating wireless sensor networks. University of Southampton e.g. is to develop technology to monitor glacier behaviour using sensor networks contributing to fundamental research in glaciology and wireless sensor networks. Coalesenses GmbH (Germany) and ETH Zurich are working in applying wireless sensor networks in many different areas too. A Spanish solution will be the one examined more thoroughly for being innovative, adaptable and multipurpose. This study of the sensor has been focused mainly to traffic applications but it cannot be forgotten the more than 50 different application compilation that has been published by this specific sensor’s firm. Currently there are many vehicle surveillance technologies including loop sensors, video cameras, image sensors, infrared sensors, microwave radar, GPS, etc. The performance is acceptable but not sufficient because of their limited coverage and expensive costs of implementation and maintenance, specially the last one. They have defects such as: line-ofsight, low exactness, depending on environment and weather, cannot perform no-stop work whether daytime or night, high costs for installation and maintenance, etc. Consequently, in actual traffic applications the received data is insufficient or bad in terms of real-time owed to detector quantity and cost. With the increase of vehicle in urban road networks, the vehicle detection technologies are confronted with new requirements. Wireless sensor network is the state of the art technology and a revolution in remote information sensing and collection applications. It has broad prospect of application in intelligent transportation system. An application for target tracking and counting using a network of binary sensors has been developed. This would allow the appliance to spend much less energy when transmitting information and to make more independent devices in order to have a better traffic control. The application is focused on the efficacy of collaborative tracking rather than on the communication protocols used by the sensor nodes. Holiday crowds are a good case in which it is necessary to keep count of the cars on the roads. To this end a Matlab simulation has been produced for target tracking and counting using a network of binary sensors that e.g. could be implemented in Libelium’s solution. Libelium is the enterprise that has developed the sensor that will be deeply examined. This would allow the appliance to spend much less energy when transmitting information and to make more independent devices. The promising results obtained indicate that binary proximity sensors can form the basis for a robust architecture for wide area surveillance and tracking. When the target paths are smooth enough ClusterTrack particle filter algorithm gives excellent performance in terms of identifying and tracking different target trajectories. This algorithm could, of course, be used for different applications and that could be done in future researches. It is not surprising that binary proximity sensor networks have attracted a lot of attention lately. Despite the minimal information a binary proximity sensor provides, networks of these sensing modalities can track all kinds of different targets classes accurate enough.

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As wireless sensor networks are usually deployed in unattended areas, security policies cannot be updated in a timely fashion upon identification of new attacks. This gives enough time for attackers to cause significant damage. Thus, it is of great importance to provide protection from unknown attacks. However, existing solutions are mostly concentrated on known attacks. On the other hand, mobility can make the sensor network more resilient to failures, reactive to events, and able to support disparate missions with a common set of sensors, yet the problem of security becomes more complicated. In order to address the issue of security in networks with mobile nodes, we propose a machine learning solution for anomaly detection along with the feature extraction process that tries to detect temporal and spatial inconsistencies in the sequences of sensed values and the routing paths used to forward these values to the base station. We also propose a special way to treat mobile nodes, which is the main novelty of this work. The data produced in the presence of an attacker are treated as outliers, and detected using clustering techniques. These techniques are further coupled with a reputation system, in this way isolating compromised nodes in timely fashion. The proposal exhibits good performances at detecting and confining previously unseen attacks, including the cases when mobile nodes are compromised.

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Wireless sensor networks (WSNs) appeal to a wide range of applications that involve the monitoring of various physical phenomena. However, WSNs are subject to many threats. In particular, lack of pervasive tamper-resistant hardware results in sensors being easy targets for compromise. Having compromised a sensor, the adversary learns all the sensor secrets, allowing it to later encrypt/decrypt or authenticate messages on behalf of that sensor. This threat is particularly relevant in the novel unattended wireless sensor networks (UWSNs) scenario. UWSNs operate without constant supervision by a trusted sink. UWSN?s unattended nature and increased exposure to attacks prompts the need for special techniques geared towards regaining security after being compromised. In this article, we investigate cooperative self-healing in UWSNs and propose various techniques to allow unattended sensors to recover security after compromise. Our techniques provide seamless healing rates even against a very agile and powerful adversary. The effectiveness and viability of our proposed techniques are assessed by thorough analysis and supported by simulation results. Finally, we introduce some real-world issues affecting UWSN deployment and provide some solutions for them as well as a few open problems calling for further investigation.

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Improving energy efficiency in buildings is one of the goals of the Smart City initiatives and a challenge for the European Union. This paper presents a 6LoWPAN wireless transducer network (BatNet) as part of an open energy management system. This network has been designed to operate in buildings, to collect environmental information (temperature, humidity, illumination and presence) and electrical consumption in real time (voltage, current and power factor). The system has been implemented and tested in the Energy Efficiency Research Facility at CeDInt-UPM.

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Energy efficiency is a major design issue in the context of Wireless Sensor Networks (WSN). If data is to be sent to a far-away base station, collaborative beamforming by the sensors may help to dis- tribute the load among the nodes and reduce fast battery depletion. However, collaborative beamforming techniques are far from opti- mality and in many cases may be wasting more power than required. In this contribution we consider the issue of energy efficiency in beamforming applications. Using a convex optimization framework, we propose the design of a virtual beamformer that maximizes the network's lifetime while satisfying a pre-specified Quality of Service (QoS) requirement. A distributed consensus-based algorithm for the computation of the optimal beamformer is also provided

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Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained.

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Environmental monitoring has become a key aspect in food production over the last few years. Due to their low cost, low power consumption and flexibility, Wireless Sensor Networks (WSNs) have turned up as a very convenient tool to be used in these environments where no intrusion is a must. In this work, a WSN application in a food factory is presented. The paper gives an overview of the system set up, covering from the initial study of the parameters and sensors, to the hardware-software design and development needed for the final tests in the factory facilities.

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Wireless Sensor Networks (WSNs) are generally used to collect information from the environment. The gathered data are delivered mainly to sinks or gateways that become the endpoints where applications can retrieve and process such data. However, applications would also expect from a WSN an event-driven operational model, so that they can be notified whenever occur some specific environmental changes instead of continuously analyzing the data provided periodically. In either operational model, WSNs represent a collection of interconnected objects, as outlined by the Internet of Things. Additionally, in order to fulfill the Internet of Things principles, Wireless Sensor Networks must have a virtual representation that allows indirect access to their resources, a model that should also include the virtualization of event sources in a WSN. Thus, in this paper a model for a virtual representation of event sources in a WSN is proposed. They are modeled as internet resources that are accessible by any internet application, following an Internet of Things approach. The model has been tested in a real implementation where a WSN has been deployed in an open neighborhood environment. Different event sources have been identified in the proposed scenario, and they have been represented following the proposed model.

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Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power.

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Recently, the cross-layer design for the wireless sensor network communication protocol has become more and more important and popular. Considering the disadvantages of the traditional cross-layer routing algorithms, in this paper we propose a new fuzzy logic-based routing algorithm, named the Balanced Cross-layer Fuzzy Logic (BCFL) routing algorithm. In BCFL, we use the cross-layer parameters’ dispersion as the fuzzy logic inference system inputs. Moreover, we give each cross-layer parameter a dynamic weight according the value of the dispersion. For getting a balanced solution, the parameter whose dispersion is large will have small weight, and vice versa. In order to compare it with the traditional cross-layer routing algorithms, BCFL is evaluated through extensive simulations. The simulation results show that the new routing algorithm can handle the multiple constraints without increasing the complexity of the algorithm and can achieve the most balanced performance on selecting the next hop relay node. Moreover, the Balanced Cross-layer Fuzzy Logic routing algorithm can adapt to the dynamic changing of the network conditions and topology effectively.

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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.