Smart-antenna techniques for energy-efficient wireless sensor networks used in bridge structural health monitoring

Abstract: It is well known that wireless sensor networks differ from other computing platforms in that 1- they typically require a minimal amount of computing power at the nodes; 2- it is often desirable for sensor nodes to have drastically low power consumption. The main benefit of the this work is a substantial network life before batteries need to be replaced or, alternatively, the capacity to function off of modest environmental energy sources (energy harvesting). In the context of Structural Health Monitoring (SHM), battery replacement is particularly problematic since nodes can be in difficult to access locations. Furthermore, any intervention on a bridge may disrupt normal bridge operation, e.g. traffic may need to be halted. In this regard, switchbeam smart antennas in combination with wireless sensor networks (WSNs) have shown great potential in reducing implementation and maintenance costs of SHM systems. The main goal of implementing switch-beam smart antennas in our application is to reduce power consumption, by focusing the radiated energy only where it is needed. SHM systems capture the dynamic vibration information of a bridge structure in real-time in order to assess the health of the structure and to predict failures. Current SHM systems are based on piezoelectric patch sensors. In addition, the collection of data from the plurality of sensors distributed over the span of the bridge is typically performed through an expensive and bulky set of shielded wires which routes the information to a data sink at one end of the structure. The installation, maintenance and operational costs of such systems are extremely high due to high power consumption and the need for periodic maintenance. Wireless sensor networks represent an attractive alternative, in terms of cost, ease of maintenance, and power consumption. However, network lifetime in terms of node battery life must be very long (ideally 5–10 years) given the cost and hassle of manual intervention. In this context, the focus of this project is to reduce the global power consumption of the SHM system by implementing switched-beam smart antennas jointly with an optimized MAC layer. In the first part of the thesis, a sensor network platform for bridge SHM incorporating switched-beam antennas is modelled and simulated. where the main consideration is the joint optimization of beamforming parameters, MAC layer, and energy consumption. The simulation model, built within the Omnet++ network simulation framework, incorporates the energy consumption profiles of actual selected components (microcontroller, radio interface chip). The energy consumption and packet delivery ratio (PDR) of the network with switched-beam antennas is compared with an equivalent network based on omnidirectional antennas. In the second part of the thesis, this system model is leveraged to examine two distinct but interrelated aspects: Gallium Arsenide (GaAs) based solar energy harvesting and switched-beam antenna strategies. The main consideration here is the joint optimization of solar energy harvesting and switchedbeam directional antennas, where an equivalent network based on omnidirectional antennas acts as a baseline reference for comparison purposes.Il est bien connu que les réseaux de capteurs sans fils diffèrent des autres plateformes informatiques étant donné 1- qu’ils requièrent typiquement une puissance de calcul minimale aux noeuds du réseau ; 2- qu’il est souvent désirable que les noeuds capteurs aient une consommation d’énergie dramatiquement faible. La principale retombée de ce travail réside en la durée de vie allongée du réseau avant que les piles ne doivent être remplacées ou, alternativement, la capacité de fonctionner indéfiniment à partir de modestes sources d’énergie ambiente (glânage d’énergie). Dans le contexte du contrôle de la santé structurale (CSS), le remplacement de piles est particulièrement problématique puisque les noeuds peuvent se trouver en des endroits difficiles d’accès. De plus, toute intervention sur un pont implique une perturbation de l’opération normale de la structure, par exemple un arrêt du traffic. Dans ce contexte, les antennes intelligentes à commutation de faisceau en combinaison avec les réseaux de capteurs sans fils ont démontré un grand potentiel pour réduire les coûts de réalisation et d’entretien de systèmes de CSS. L’objectif principal de l’intégration d’antennes à commutation de faisceau dans notre application réside dans la réduction de la consommation énergétique, réalisée en concentrant l’énergie radiée uniquement là où elle est nécessaire. Les systèmes de CSS capturent l’information dynamique de vibration d’une structure de pont en temps réel de manière à évaluer la santé de la structure et prédire les failles. Les systèmes courants de CSS sont basés sur des senseurs piézoélectriques planaires. De plus, la collecte de données à partir de la pluralité de senseurs distribués sur l’étendue du pont est typiquement effectuée par le biais d’un ensemble coûteux et encombrant de câbles blindés qui véhiculent l’information jusqu’à un point de collecte à une extremité de la structure. L’installation, l’entretien, et les coûts opérationnels de tels systèmes sont extrêmement élevés étant donné la consommation de puissance élevée et le besoin d’entretien régulier. Les réseaux de capteurs sans fils représentent une alternative attrayante, en termes de coût, facilité d’entretien et consommation énergétique. Toutefois, la vie de réseau en termes de la durée de vie des piles doit être très longue (idéalement de 5 à 10 ans) étant donné le coût et les problèmes liés à l’intervention manuelle. Dans ce contexte, ce projet se concentre sur la réduction de la consommation de puissance globale d’un système de CSS en y intégrant des antennes intelligentes à commutation de faisceau conjointement avec une couche d’accès au médium (couche MAC) optimisée. Dans la première partie de la thèse, une plateforme de réseau de capteurs sans fils pour le CSS d’un pont incorporant des antennes à commutation de faisceaux est modélisé et simulé, avec pour considération principale l’optimisation des paramètres de sélection de faisceau, de la couche MAC et de la consommation d’énergie. Le modèle de simulation, construit dans le logiciel de simulation de réseaux Omnet++, incorpore les profils de consommation d’énergie de composants réels sélectionnés (microcontrôleur, puce d’interface radio). La consommation d’énergie et le taux de livraison de paquets du réseau avec antennes à commutation de faisceau est comparé avec un réseau équivalent basé sur des antennes omnidirectionnelles. Dans la deuxième partie de la thèse, le modèle système proposé est mis à contribution pour examiner deux aspects distrincts mais interreliés : le glânage d’énergie à partir de cellules solaire à base d’arséniure de Gallium (GaAs) et les stratégies liées aux antennes à commutation de faisceau. La considération principale ici est l’optimisation conjointe du glânage d’énergie et des antennes à commutation de faisceau, en ayant pour base de comparaison un réseau équivalent à base d’antennes omnidirectionnelles

Interference Mitigation in Multi-Hop Wireless Networks with Advanced Physical-Layer Techniques

In my dissertation, we focus on the wireless network coexistence problem with advanced physical-layer techniques. For the first part, we study the problem of Wireless Body Area Networks (WBAN)s coexisting with cross-technology interference (CTI). WBANs face the RF cross-technology interference (CTI) from non-protocol-compliant wireless devices. Werst experimentally characterize the adverse effect on BAN caused by the CTI sources. Then we formulate a joint routing and power control (JRPC) problem, which aims at minimizing energy consumption while satisfying node reachability and delay constraints. We reformulate our problem into a mixed integer linear programing problem (MILP) and then derive the optimal results. A practical JRPC protocol is then proposed. For the second part, we study the coexistence of heterogeneous multi-hop networks with wireless MIMO. We propose a new paradigm, called cooperative interference mitigation (CIM), which makes it possible for disparate networks to cooperatively mitigate the interference to/from each other to enhance everyone\u27s performance. We establish two tractable models to characterize the CIM behaviors of both networks by using full IC (FIC) and receiver-side IC (RIC) only. We propose two bi-criteria optimization problems aiming at maximizing both networks\u27 throughput, while cooperatively canceling the interference between them based on our two models. In the third and fourth parts, we study the coexistence problem with MIMO from a different point of view: the incentive of cooperation. We propose a novel two-round game framework, based on which we derive two networks\u27 equilibrium strategies and the corresponding closed-form utilities. We then extend our game-theoretical analysis to a general multi-hop case, specifically the coexistence problem between primary network and multi-hop secondary network in the cognitive radio networks domain. In the final part, we study the benefits brought by reconfigurable antennas (RA). We systematically exploit the pattern diversity and fast reconfigurability of RAs to enhance the throughput of MWNs. Werst propose a novel link-layer model that captures the dynamic relations between antenna pattern, link coverage and interference. Based on our model, a throughput optimization framework is proposed by jointly considering pattern selection and link scheduling, which is formulated as a mixed integer non-linear programming problem

Intrusion Detection System for Platooning Connected Autonomous Vehicles

The deployment of Connected Autonomous Vehicles (CAVs) in Vehicular Ad Hoc Networks (VANETs) requires secure wireless communication in order to ensure reliable connectivity and safety. However, this wireless communication is vulnerable to a variety of cyber atacks such as spoofing or jamming attacks. In this paper, we describe an Intrusion Detection System (IDS) based on Machine Learning (ML) techniques designed to detect both spoofing and jamming attacks in a CAV environment. The IDS would reduce the risk of traffic disruption and accident caused as a result of cyber-attacks. The detection engine of the presented IDS is based on the ML algorithms Random Forest (RF), k-Nearest Neighbour (k-NN) and One-Class Support Vector Machine (OCSVM), as well as data fusion techniques in a cross-layer approach. To the best of the authors’ knowledge, the proposed IDS is the first in literature that uses a cross-layer approach to detect both spoofing and jamming attacks against the communication of connected vehicles platooning. The evaluation results of the implemented IDS present a high accuracy of over 90% using training datasets containing both known and unknown attacks

Propagation, Localization and Navigation in Tunnel-like Environments

La robótica de servicio, entendida como aquella destinada al uso de uno o varios robots con fines de, por ejemplo, vigilancia, rescate e inspecciones, ha ido tomando cada vez más relevancia en los últimos años. Debido a los grandes avances en las distintas áreas de la robótica, los robots han sido capaces de ejecutar satisfactoriamente tareas que resultan peligrosas o incluso imposibles para los humanos, en diversos entornos. Entre ellos, los entornos confinados como túneles, minas y tuberías, han atraído la atención en aplicaciones relacionadas con transporte ferroviario, redes vehiculares, búsqueda y rescate, y vigilancia, tanto en el ámbito civil como militar. En muchas tareas, la utilización de varios robots resulta más provechoso que utilizar sólo uno. Para cooperar, los robots deben intercambiar información sobre el entorno y su propio estado, por lo que la comunicación entre ellos resulta crucial. Debido a la imposibilidad de utilizar redes cableadas entre robots móviles, se despliegan redes inalámbricas. Para determinar la calidad de señal entre dos robots, inicialmente se utilizaban modelos de propagación basados únicamente en la distancia entre ellos. Sin embargo, estas predicciones sólo resultan útiles en exteriores y sin la presencia de obstáculos, que sólo componen una pequeña parte de los escenarios de la robótica de servicio. Mas aún, la naturaleza altamente multi-trayecto de la propagación electromagnética en túneles hace que éstos actúen como guías de onda para cierto rango de frecuencias, extendiendo considerablemente el alcance de comunicación en comparación con entornos exteriores. Sin embargo, la señal se ve afectada con profundos desvanecimientos (llamados fadings en inglés). Esto los convierte en un reto para la robótica que considera la comunicación entre robots como fundamental. Además, la naturaleza hostil de estos entornos, así como también la falta de características visuales y estructurales, dificultan la localización en estos escenarios, cuestión que resulta fundamental para ejecutar con éxito una tarea con un robot. Los métodos de localización utilizados en interiores, como aquellos basados en SLAM visual, resultan imprecisos por la falta de características distintivas para cámaras o lásers, mientras que los sensores utilizados en exteriores, como el GPS, no funcionan dentro de túneles o tuberías. En esta tesis abordamos problemas fundamentales para la robótica con el fin de proporcionar herramientas necesarias para la exploración con robots en entornos tipo túnel, manteniendo la conectividad de la red de comunicaciones formada por varios robots y una estación base. Para ello, primeramente caracterizamos, en términos de propagación, los dos escenarios tipo túnel más comunes: un túnel de hormigón y una tubería metálica. Hacemos énfasis en el fenómeno de los fadings, ya que son el problema más importante a considerar para mantener la comunicación. Posteriormente presentamos una estrategia de navegación para desplegar un equipo de robots en un túnel, lidiando con los fadings para mantener la conectividad de la red formada por los robots. Esta estrategia ha sido validada a través de numerosos experimentos realizados en un túnel real, el túnel de Somport. Luego, abordamos el problema de la localización, proponiendo e implementando una técnica que permite estimar la posición de un robot dentro de una tubería, basada en la periodicidad de los fadings. El método es validado a través de experimentos reales en tuberías de pequeña y grandes dimensiones. Finalmente, proponemos esquemas de diversidad espacial, de forma que se facilita la navegación mientras se mejora la localización.Deploying a team of robots for search and rescue, inspection, or surveillance, has increasingly gained attention in the last years. As a result of the advances in several areas of robotics, robots have been able to successfully execute tasks that are hazardous or even impossible for humans in a variety of scenarios, such as outdoors, indoors, or even underground. Among these scenarios, tunnel-like environments (such as tunnels, mines, or pipes) have attracted attention for train applications, vehicular networks, search and rescue, and even service and surveillance missions in both military and civilian contexts. In most of the tasks, utilizing a multi-robot team yields better results than a singlerobot system, as it makes the system more robust while reducing the time required to complete tasks. In order to cooperate, robots must exchange information about their current state and the surrounding environment, making communication between them a crucial task. However, due to the mobile nature of robots used for exploration, a wired architecture is not possible nor convenient. Instead, a wireless network is often deployed. Wireless propagation in tunnel-like environments, characterized for the presence of strong fading phenomena, differs from regular indoor and outdoor scenarios, posing multiple challenges for communication-aware robotics. In addition, accurate localization is a problem in environments such as tunnels or pipes. These environments generally lack distinctive visual and/or structural features and are longer than they are wide in shape. Standard indoor localization techniques do not perform well in pipelines or tunnels given the lack of exploitable features, while outdoor techniques (GPS in particular) do not work in these scenarios. In this thesis, we address basic robotics-related problems in order to provide some tools necessary for robotics exploration in tunnel-like scenarios under connectivity constraints. In the first part, we characterize, in terms of propagation, two of the most common tunnel-like environments: a pipe and a tunnel. We emphasize the spatial-fadings phenomena, as it is one of the most relevant issues to deal with, in a communications context. Secondly, we present a navigation strategy to deploy a team of robots for tunnel exploration, in particular maintaining network connectivity in the presence of these fadings. Several experiments conducted in a tunnel allow us to validate the connectivity maintenance of the system. Next, we address the localization problem and propose a technique that uses the periodicity of the fadings to estimate the position of the robots from the base station. The method is validated in small-scale and large-scale pipes. Finally, we propose spatial diversity schemes in order to ease the navigation while improving the localization

Machine Learning for Intrusion Detection into Unmanned Aerial System 6G Networks

Progress in the development of wireless network technology has played a crucial role in the evolution of societies and provided remarkable services over the past decades. It remotely offers the ability to execute critical missions and effective services that meet the user\u27s needs. This advanced technology integrates cyber and physical layers to form cyber-physical systems (CPS), such as the Unmanned Aerial System (UAS), which consists of an Unmanned Aerial Vehicle (UAV), ground network infrastructure, communication link, etc. Furthermore, it plays a crucial role in connecting objects to create and develop the Internet of Things (IoT) technology. Therefore, the emergence of the CPS and IoT technologies provided many connected devices, generating an enormous amount of data. Consequently, the innovation of 6G technology is an urgent issue in the coming years. The 6G network architecture is an integration of the satellite network, aerial networks, terrestrial networks, and marine networks. These integrated network layers will provide new enabling technologies, for example, air interfaces and transmission technology. Therefore, integrating heterogeneous network layers guarantees an expansion strategy in the capacity that leads to low latency, ultra-high throughput, and high data rates. In the 6G network, Unmanned Aerial Vehicles (UAVs) are expected to densely occupy aerial spaces as UAV flying base stations (UAV-FBS) that comprise the aerial network layer to offer ubiquitous connectivity and enhance the terrestrial network in remote areas where it is challenging to deploy traditional infrastructure, for example, mountain, ocean deserts, and forest. Although the aerial network layer offers benefits to facilitate governmental and commercial missions, adversaries exploit network vulnerabilities to block intercommunication among nodes by jamming attacks and violating integrity through executing spoofing attacks. This work offers a practical IDS onboard UAV intrusion detection system to detect unintentional interference, intentional interference jamming, and spoofing attacks. Integrating time series data with machine learning models is the main part of the suggested IDF to detect anomalies accurately. This integration will improve the accuracy and effectiveness of the model. The 6G network is expected to handle a high volume of data where non-malicious interference and congestion in the channel are similar to a jamming attack. Therefore, an efficient anomaly detection technique must distinguish behaviors in the drone\u27s wireless network as normal or abnormal behavior. Our suggested model comprises two layers. The first layer has the algorithm to detect the anomaly during transmission. Then it will send the initial decision to the second layer in the model, including two separated algorithms, confirming the initial decision separately (nonintentional interference such as congestion in the channel, intentional interference jamming attack, and classify the type of jamming attack, and the second algorithm confirms spoofing attack. A jamming attack is a stealthy attack that aims to exhaust battery level or block communication to make wireless UAV networks unavailable. Therefore, the UAV forcibly relies on GPS signals. In this case, the adversary triggers a spoofing attack by manipulating the Global Navigation Satellite System (GNSS) signal and sending a fake signal to make UAVs estimate incorrect positions and deviate from their planning path to malicious zones. Hackers can start their malicious action either from malicious UAV nodes or the terrestrial malicious node; therefore, this work will enhance security and pave the way to start thinking about leveraging the benefit of the 6G network to design robust detection techniques for detecting multiple attacks that happen separately or simultaneously

Improving Wifi Sensing And Networking With Channel State Information

In recent years, WiFi has a very rapid growth due to its high throughput, high efficiency, and low costs. Multiple-Input Multiple-Output (MIMO) and Orthogonal Frequency-Division Multiplexing (OFDM) are two key technologies for providing high throughput and efficiency for WiFi systems. MIMO-OFDM provides Channel State Information (CSI) which represents the amplitude attenuation and phase shift of each transmit-receiver antenna pair of each carrier frequency. CSI helps WiFi achieve high throughput to meet the growing demands of wireless data traffic. CSI captures how wireless signals travel through the surrounding environment, so it can also be used for wireless sensing purposes. This dissertation presents how to improve WiFi sensing and networking with CSI. More specifically, this dissertation proposes deep learning models to improve the performance and capability of WiFi sensing and presents network protocols to reduce CSI feedback overhead for high efficiency WiFi networking. For WiFi sensing, there are many wireless sensing applications using CSI as the input in recent years. To get a better understanding of existing WiFi sensing technologies and future WiFi sensing trends, this dissertation presents a survey of signal processing techniques, algorithms, applications, performance results, challenges, and future trends of CSI-based WiFi sensing. CSI is widely used for gesture recognition and sign language recognition. Existing methods for WiFi-based sign language recognition have low accuracy and high costs when there are more than 200 sign gestures. The dissertation presents SignFi for sign language recognition using CSI and Convolutional Neural Networks (CNNs). SignFi provides high accuracy and low costs for run-time testing for 276 sign gestures in the lab and home environments. For WiFi networking, although CSI provides high throughput for WiFi networks, it also introduces high overhead. WiFi transmitters need CSI feedback for transmit beamforming and rate adaptation. The size of CSI packets is very large and it grows very fast with respect to the number of antennas and channel width. CSI feedback introduces high overhead which reduces the performance and efficiency of WiFi systems, especially mobile and hand-held WiFi devices. This dissertation presents RoFi to reduce CSI feedback overhead based on the mobility status of WiFi receivers. CSI feedback compression reduces overhead, but WiFi receivers still need to send CSI feedback to the WiFi transmitter. The dissertation presents EliMO for eliminating CSI feedback without sacrificing beamforming gains

A Review of Radio Frequency Based Localization for Aerial and Ground Robots with 5G Future Perspectives

Efficient localization plays a vital role in many modern applications of Unmanned Ground Vehicles (UGV) and Unmanned aerial vehicles (UAVs), which would contribute to improved control, safety, power economy, etc. The ubiquitous 5G NR (New Radio) cellular network will provide new opportunities for enhancing localization of UAVs and UGVs. In this paper, we review the radio frequency (RF) based approaches for localization. We review the RF features that can be utilized for localization and investigate the current methods suitable for Unmanned vehicles under two general categories: range-based and fingerprinting. The existing state-of-the-art literature on RF-based localization for both UAVs and UGVs is examined, and the envisioned 5G NR for localization enhancement, and the future research direction are explored

Improving the performance of wireless sensor networks using directional antennas

Over the last decades, lots of new applications have emerged thanks to the availability of small devices capable of wireless communications that form Wireless Sensor Networks (WSNs). These devices allow sensing, processing, and communication of multiple physical variables while keeping a low power consumption. During the last years, most of the research efforts were spent on the development and optimization of wireless communication protocols, aiming to maximize the reliability of the network while achieving the lowest possible power consumption. In this thesis, we study how to improve the performance of these WSNs by using directional antennas. Directional antennas can provide a higher gain and reduce the interference with other nodes by concentrating the radiated power in a certain direction. We present the different kinds of directional antennas available for WSNs, and we select the 6-element SPIDA antenna as a case of study. We present an electromagnetic model of this antenna, and we incorporate it into the COOJA network simulator. We report the first complete characterization of this antenna, including the radiation pattern and S11 parameters. The characterization shows that the antenna has a maximum gain of 6.8 dBi, a Half-Power Beamwidth (HPBW) of 113° and a module of S11 parameter of -7.5 dB at the central frequency (fc = 2.4525 GHz). We also present a novel way to optimize the antenna without changing its design by isolating multiple director elements. We show that with this technique, the performance of the antenna can be improved in terms of maximum gain, narrower HPBW, and a lower module of the S11 parameter without making any changes in the antenna itself. We evaluate the impact of supporting directional communications in the different layers of the network stack. We analyze the different challenges that arise and propose optimizations to overcome them in order to take advantage of the benefits of directional communication. We present an analysis of the state-of-the-art in neighbor discovery protocols for WSNs with directional antennas, and we propose, implement end evaluate two novel fully directional protocols: Q-SAND and DANDi. We compare both of them with SAND, a fully directional neighbor discovery protocol. DANDi is a fully directional asynchronous and dynamic neighbor discovery protocol where the contention resolution relies on a collision detection mechanism. To the best of our knowledge, DANDi is the fastest neighbor discovery protocol for WSN with directional antennas, with the additional advantage of being able to discover every reliable communication link in a network without requiring any prior information of the network topology. We combine the directional neighbor discovery protocol with MAC and routing optimizations in order fully take advantage of the benefits of using directional antennas. We focus on convergecast, a typical data collection application where every node sends packets periodically to a sink node. We present DirMAC, a novel MAC protocol that fully supports directional communication, together with four different heuristics to optimize the performance of the protocols. One of these heuristics has the added major benefit of being completely distributed and with no need for offline processing. Our evaluation shows that optimizations at both the MAC and routing layers are needed in order to reap the benefits of using directional antennas for convergecast. Our results show that the performance of the network can be greatly improved in terms of packet delivery rate, energy consumption, and energy per received packet, and that we obtain the largest performance improvements in networks with dense traffic. Simulations with different node densities show that when using directional antennas the PDR increases up to 29%, while energy consumption and energy per received packet decreases by up to 55% and 46% respectively. Experiments with real nodes validate these results showing a significant performance increase when using directional antennas in our scenarios, with a reduction in the RDC and EPRP of 25% and 15% respectively, while maintaining a PDR of 100%.Durante las últimas décadas, la disponibilidad de pequeños dispositivos con comunicación inalámbrica ha permitido el desarrollo de muchas nuevas aplicaciones. Estos dispositivos forman Redes de Sensores Inalámbricos (RSI, o WSN por sus siglas en inglés) que permiten sensar, procesar y comunicar datos provenientes de variables físicas, mientras que mantienen un bajo consumo energético. En los últimos años, la mayor parte de los esfuerzos de la comunidad científica estuvieron concentrados en el desarrollo y optimización de los protocolos de comunicación inalámbricos, buscando maximizar la confiabilidad de la red y minimizar el consumo energético. En esta tesis estudiamos cómo mejorar el rendimiento de las RSI usando antenas direccionales. Las antenas direccionales pueden proporcionar una mayor ganancia y reducir la interferencia con otros nodos al concentrar la potencia radiada en una cierta dirección. Comenzamos presentando los distintos tipos de antenas direccionales disponibles para las RSI, y seleccionamos la antena SPIDA de 6 elementos como caso de estudio. Luego presentamos un modelo electromagnético de la antena, que incorporamos al simulador de red COOJA. Construimos un primer prototipo con el que realizamos la primera caracterización completa de ésta antena, incluyendo el patrón de radiación y el parámetro S11. La caracterización muestra que la antena tiene una ganancia máxima de 6,8 dBi, un ancho de haz a mitad de potencia (HPBW por sus siglas en inglés) de 113° y un módulo del parámetro S11 de -7,5 dB en la frecuencia central (fc = 2,4525 GHz). También mostramos una forma innovadora de optimizar la antena sin cambiar su diseño utilizando varios elementos directores al mismo tiempo. Mostramos que con esta técnica se puede mejorar el rendimiento de la antena en términos de ganancia máxima, ancho de haz a mitad de potencia, y módulo del parámetro S11. Luego evaluamos el impacto de usar comunicaciones direccionales en las diferentes capas del stack de red. Analizamos los diferentes desafíos que surgen y proponemos optimizaciones para sortearlos. Presentamos un análisis del estado del arte en protocolos de descubrimiento de vecinos en RSI con antenas direccionales, y proponemos, implementamos y evaluamos dos protocolos direccionales : Q-SAND y DANDi. DANDi es un protocolo de descubrimiento de vecinos direccional, asíncrono y dinámico, donde la contienda por el canal se resuelve con un mecanismo basado en la detección de colisiones. Hasta donde sabemos, DANDi es el protocolo de descubrimiento de vecinos más rápido para RSI con antenas direccionales, con la ventaja adicional de que permite descubrir todos los enlaces de comunicación confiables de una red sin requerir ningún conocimiento previo de la topología. Luego combinamos los protocolos de descubrimiento de vecinos con optimizaciones en las capas de ruteo y acceso al medio para construir una aplicación de recolección de datos, donde cada nodo envía paquetes periódicamente a un nodo centralizador. Presentamos DirMAC, un protocolo de acceso al medio innovador que soporta comunicaciones direccionales, junto con cuatro heurísticas que permiten optimizar el rendimiento de los protocolos (una de ellas con la ventaja adicional que es totalmente distribuida). Los resultados muestran que usar antenas direccionales en este tipo de aplicaciones permite mejorar sustancialmente el rendimiento de la red, mostrando las mayores mejoras en redes con alto tráfico. Las simulaciones con diferentes densidades de nodos muestran que al usar antenas direccionales se puede aumentar el ratio de entrega de paquetes en hasta 29%, mientras que el consumo energético y la energía por paquete recibido bajan en hasta 55% y 46% respectivamente. Los experimentos en nodos reales validan estos resultados, mostrando una reducción en el consumo energético y en la energía por paquete recibido de 25% y 15% respectivamente, mientras que mantienen un ratio de entrega de paquetes de 100%