Actas da 10ª Conferência sobre Redes de Computadores

Universidade do MinhoCCTCCentro AlgoritmiCisco SystemsIEEE Portugal Sectio

Architecture and communication protocol to monitor and control water quality and irrigation in agricultural environments

[ES] La introducción de soluciones tecnológicas en la agricultura permite reducir el uso de recursos y aumentar la producción de los cultivos. Además, la calidad del agua de regadío se puede monitorizar para asegurar la seguridad de los productos para el consumo humano. Sin embargo, la localización remota de la mayoría de los campos presenta un problema para proveer de cobertura inalámbrica a los nodos sensores y actuadores desplegados en los campos y los canales de agua para regadío. El trabajo presentado en esta tesis aborda el problema de habilitar la comunicación inalámbrica entre los dispositivos electrónicos desplegados para la monitorización de la calidad del agua y el campo a través de un protocolo de comunicación y arquitectura heterogéneos. La primera parte de esta tesis introduce los sistemas de agricultura de precisión (PA) y la importancia de la monitorización de la calidad del agua y el campo. Asimismo, las tecnologías que permiten la comunicación inalámbrica en sistemas PA y el uso de soluciones alternativas como el internet de las cosas bajo tierra (IoUT) y los vehículos aéreos no tripulados (UAV) se introducen también. Después, se realiza un análisis en profundidad del estado del arte respecto a los sensores para la monitorización del agua, el campo y las condiciones meteorológicas, así como sobre las tecnologías inalámbricas más empleadas en PA. Además, las tendencias actuales y los desafíos de los sistemas de internet de las cosas (IoT) para regadío, incluyendo las soluciones alternativas introducidas anteriormente, han sido abordados en detalle. A continuación, se presenta la arquitectura propuesta para el sistema, la cual incluye las áreas de interés para las actividades monitorización que incluye las áreas de los canales y el campo. A su vez, la descripción y los algoritmos de operación de los nodos sensores contemplados para cada área son proporcionados. El siguiente capítulo detalla el protocolo de comunicación heterogéneo propuesto, incluyendo los mensajes y alertas del sistema. Adicionalmente, se presenta una nueva topología de árbol para redes híbridas LoRa/WiFi multisalto. Las funcionalidades específicas adicionales concebidas para la arquitectura propuesta están descritas en el siguiente capítulo. Éstas incluyen algoritmos de agregación de datos para la topología propuesta, un esquema de las amenazas de seguridad para los sistemas PA, algoritmos de ahorro de energía y tolerancia a fallos, comunicación bajo tierra para IoUT y el uso de drones para adquisición de datos. Después, los resultados de las simulaciones para las soluciones propuestas anteriormente son presentados. Finalmente, se tratan las pruebas realizadas en entornos reales para el protocolo heterogéneo presentado, las diferentes estrategias de despliegue de los nodos empleados, el consumo energético y la función de cuantificación de fruta. Estas pruebas demuestran la validez de la arquitectura y protocolo de comunicación heterogéneos que se han propuesto.[CA] La introducció de solucions tecnològiques en l'agricultura permet reduir l'ús de recursos i augmentar la producció dels cultius. A més, la qualitat de l'aigua de regadiu es pot monitoritzar per assegurar la qualitat dels productes per al consum humà. No obstant això, la localització remota de la majoria dels camps presenta un problema per a proveir de cobertura sense fils als nodes sensors i actuadors desplegats als camps i els canals d'aigua per a regadiu. El treball presentat en aquesta tesi tracta el problema d'habilitar la comunicació sense fils entre els dispositius electrònics desplegats per a la monitorització de la qualitat de l'aigua i el camp a través d'un protocol de comunicació i arquitectura heterogenis. La primera part d'aquesta tesi introdueix els sistemes d'agricultura de precisió (PA) i la importància de la monitorització de la qualitat de l'aigua i el camp. Així mateix, també s'introdueixen les tecnologies que permeten la comunicació sense fils en sistemes PA i l'ús de solucions alternatives com l'Internet de les coses sota terra (IoUT) i els vehicles aeris no tripulats (UAV). Després, es realitza una anàlisi en profunditat de l'estat de l'art respecte als sensors per a la monitorització de l'aigua, el camp i les condicions meteorològiques, així com sobre les tecnologies sense fils més emprades en PA. S'aborden les tendències actuals i els reptes dels sistemes d'internet de les coses (IoT) per a regadiu, incloent les solucions alternatives introduïdes anteriorment. A continuació, es presenta l'arquitectura proposada per al sistema, on s'inclouen les àrees d'interès per a les activitats monitorització en els canals i el camp. Finalment, es proporciona la descripció i els algoritmes d'operació dels nodes sensors contemplats per a cada àrea. El següent capítol detalla el protocol de comunicació heterogeni proposat, així como el disseny del missatges i alertes que el sistema proposa. A més, es presenta una nova topologia d'arbre per a xarxes híbrides Lora/WiFi multi-salt. Les funcionalitats específiques addicionals concebudes per l'arquitectura proposada estan descrites en el següent capítol. Aquestes inclouen algoritmes d'agregació de dades per a la topologia proposta, un esquema de les alertes de seguretat per als sistemes PA, algoritmes d'estalvi d'energia i tolerància a fallades, comunicació per a IoUT i l'ús de drons per a adquisició de dades. Després, es presenten els resultats de les simulacions per a les solucions proposades. Finalment, es duen a terme les proves en entorns reals per al protocol heterogeni dissenyat. A més s'expliquen les diferents estratègies de desplegament dels nodes empleats, el consum energètic, així com, la funció de quantificació de fruita. Els resultats d'aquetes proves demostren la validesa de l'arquitectura i protocol de comunicació heterogenis propost en aquesta tesi.[EN] The introduction of technological solutions in agriculture allows reducing the use of resources and increasing the production of the crops. Furthermore, the quality of the water for irrigation can be monitored to ensure the safety of the produce for human consumption. However, the remote location of most fields presents a problem for providing wireless coverage to the sensing nodes and actuators deployed on the fields and the irrigation water canals. The work presented in this thesis addresses the problem of enabling wireless communication among the electronic devices deployed for water quality and field monitoring through a heterogeneous communication protocol and architecture. The first part of the dissertation introduces Precision Agriculture (PA) systems and the importance of water quality and field monitoring. In addition, the technologies that enable wireless communication in PA systems and the use of alternative solutions such as Internet of Underground Things (IoUT) and Unmanned Aerial Vehicles (UAV) are introduced as well. Then, an in-depth analysis on the state of the art regarding the sensors for water, field and meteorology monitoring and the most utilized wireless technologies in PA is performed. Furthermore, the current trends and challenges for Internet of Things (IoT) irrigation systems, including the alternate solutions previously introduced, have been discussed in detail. Then, the architecture for the proposed system is presented, which includes the areas of interest for the monitoring activities comprised of the canal and field areas. Moreover, the description and operation algorithms of the sensor nodes contemplated for each area is provided. The next chapter details the proposed heterogeneous communication protocol including the messages and alerts of the system. Additionally, a new tree topology for hybrid LoRa/WiFi multi-hop networks is presented. The specific additional functionalities intended for the proposed architecture are described in the following chapter. It includes data aggregation algorithms for the proposed topology, an overview on the security threats of PA systems, energy-saving and fault-tolerance algorithms, underground communication for IoUT, and the use of drones for data acquisition. Then, the simulation results for the solutions previously proposed are presented. Finally, the tests performed in real environments for the presented heterogeneous protocol, the different deployment strategies for the utilized nodes, the energy consumption, and a functionality for fruit quantification are discussed. These tests demonstrate the validity of the proposed heterogeneous architecture and communication protocol.García García, L. (2021). Architecture and communication protocol to monitor and control water quality and irrigation in agricultural environments [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17422

Adaptation à la mobilité dans les réseaux ad hoc

Les études protocolaires sur les réseaux multi-sauts mobiles proposent d’améliorer la performance du réseau en liant le comportement des protocoles à sa dynamique d’évolution. Le protocole s’adapte à l’état du réseau grâce à un ensemble de métriques. Ainsi pour les protocoles de routage il s’agit de trouver des chemins tout en considérant l’état énergétique des nœuds, la bande passante des liens, la qualité de service, ou encore la dynamique de la topologie qui est liée à la qualité des liens sans fil et à la mobilité des éléments du réseau. Le travail présenté traite de l’adaptation à la mobilité dans les protocoles de routage et s’intéresse aux métriques de mobilité. Dans une première étape nous analysons le processus d’adaptation en en dégageant les caractéristiques, les contraintes et l’intérêt, et étudions qualitativement les métriques de mobilité. Nous examinons différents travaux de recherche ayant pour objet la mobilité et ses métriques dont nous proposons une taxinomie originale. Nous mettons en évidence l’intérêt des métriques obtenues par mesure locale et de voisinage. Dans une deuxième étape, nous évaluons par simulation les métriques. L’objectif est de déterminer une "meilleure" métrique de mobilité, c'est-à-dire celle qui apportera le plus de gain de performance à une adaptation protocolaire. Le postulat est que plus la métrique influe sur les performances d'un protocole, plus il est intéressant que le protocole adapte son comportement en fonction de sa valeur. L’analyse de corrélation entre performances et métriques, sur plusieurs protocoles de routage, ne permet pas de mettre en avant une meilleure métrique qui soit indépendante du contexte, à savoir de la densité ou du modèle de mobilité. Nous montrons néanmoins l’intérêt de la métrique durée de liaison. Finalement, nous développons deux applications à partir des métriques sélectionnées par l’analyse. Ce sont la densité, exprimée par le nombre de voisins, ainsi que la mobilité, exprimée par la durée de liaison pour la première application, et par le nombre d’erreurs de route pour la seconde application. La première application met en place un choix adaptatif des éléments MPR (Multi-Point Relay) dans le protocole de routage Optimized Link State Routing (OLSR), la deuxième développe une élection adaptative des chefs de clusters et un changement de mode adaptatif (avec ou sans structure) pour le protocole Cluster Source Routing (CSR). Pour les deux applications plusieurs stratégies d’adaptations sont considérées ; le meilleur résultat est obtenu dans les deux cas par la stratégie d'adaptation à la mobilité en plus de la densité. Ce travail se prolonge par l’étude de validation des résultats en rapport au modèle de mobilité. Nous en déduisons une méthode pour appliquer, selon les conditions de mobilité et de densité, des adaptations

Building Blocks for IoT Analytics Internet-of-Things Analytics

Internet-of-Things (IoT) Analytics are an integral element of most IoT applications, as it provides the means to extract knowledge, drive actuation services and optimize decision making. IoT analytics will be a major contributor to IoT business value in the coming years, as it will enable organizations to process and fully leverage large amounts of IoT data, which are nowadays largely underutilized. The Building Blocks of IoT Analytics is devoted to the presentation the main technology building blocks that comprise advanced IoT analytics systems. It introduces IoT analytics as a special case of BigData analytics and accordingly presents leading edge technologies that can be deployed in order to successfully confront the main challenges of IoT analytics applications. Special emphasis is paid in the presentation of technologies for IoT streaming and semantic interoperability across diverse IoT streams. Furthermore, the role of cloud computing and BigData technologies in IoT analytics are presented, along with practical tools for implementing, deploying and operating non-trivial IoT applications. Along with the main building blocks of IoT analytics systems and applications, the book presents a series of practical applications, which illustrate the use of these technologies in the scope of pragmatic applications. Technical topics discussed in the book include: Cloud Computing and BigData for IoT analyticsSearching the Internet of ThingsDevelopment Tools for IoT Analytics ApplicationsIoT Analytics-as-a-ServiceSemantic Modelling and Reasoning for IoT AnalyticsIoT analytics for Smart BuildingsIoT analytics for Smart CitiesOperationalization of IoT analyticsEthical aspects of IoT analyticsThis book contains both research oriented and applied articles on IoT analytics, including several articles reflecting work undertaken in the scope of recent European Commission funded projects in the scope of the FP7 and H2020 programmes. These articles present results of these projects on IoT analytics platforms and applications. Even though several articles have been contributed by different authors, they are structured in a well thought order that facilitates the reader either to follow the evolution of the book or to focus on specific topics depending on his/her background and interest in IoT and IoT analytics technologies. The compilation of these articles in this edited volume has been largely motivated by the close collaboration of the co-authors in the scope of working groups and IoT events organized by the Internet-of-Things Research Cluster (IERC), which is currently a part of EU's Alliance for Internet of Things Innovation (AIOTI)

Building Blocks for IoT Analytics Internet-of-Things Analytics

Internet-of-Things (IoT) Analytics are an integral element of most IoT applications, as it provides the means to extract knowledge, drive actuation services and optimize decision making. IoT analytics will be a major contributor to IoT business value in the coming years, as it will enable organizations to process and fully leverage large amounts of IoT data, which are nowadays largely underutilized. The Building Blocks of IoT Analytics is devoted to the presentation the main technology building blocks that comprise advanced IoT analytics systems. It introduces IoT analytics as a special case of BigData analytics and accordingly presents leading edge technologies that can be deployed in order to successfully confront the main challenges of IoT analytics applications. Special emphasis is paid in the presentation of technologies for IoT streaming and semantic interoperability across diverse IoT streams. Furthermore, the role of cloud computing and BigData technologies in IoT analytics are presented, along with practical tools for implementing, deploying and operating non-trivial IoT applications. Along with the main building blocks of IoT analytics systems and applications, the book presents a series of practical applications, which illustrate the use of these technologies in the scope of pragmatic applications. Technical topics discussed in the book include: Cloud Computing and BigData for IoT analyticsSearching the Internet of ThingsDevelopment Tools for IoT Analytics ApplicationsIoT Analytics-as-a-ServiceSemantic Modelling and Reasoning for IoT AnalyticsIoT analytics for Smart BuildingsIoT analytics for Smart CitiesOperationalization of IoT analyticsEthical aspects of IoT analyticsThis book contains both research oriented and applied articles on IoT analytics, including several articles reflecting work undertaken in the scope of recent European Commission funded projects in the scope of the FP7 and H2020 programmes. These articles present results of these projects on IoT analytics platforms and applications. Even though several articles have been contributed by different authors, they are structured in a well thought order that facilitates the reader either to follow the evolution of the book or to focus on specific topics depending on his/her background and interest in IoT and IoT analytics technologies. The compilation of these articles in this edited volume has been largely motivated by the close collaboration of the co-authors in the scope of working groups and IoT events organized by the Internet-of-Things Research Cluster (IERC), which is currently a part of EU's Alliance for Internet of Things Innovation (AIOTI)

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Novel applications of Machine Learning to Network Traffic Analysis and Prediction

It is now clear that machine learning will be widely used in future telecommunication networks as it is increasingly used in today's networks. However, despite its increasing application and its enormous potential, there are still many areas in which the new techniques developed in the area of machine learning are not yet fully utilized. The aim of this thesis is to present the application of innovative techniques of machine learning (ML-Machine Learning) in the field of Telecommunications, and specifically to problems related to the analysis and prediction of traffic in data networks (NTAP - Network Traffic Analysis and Prediction). The applications of NTAP are very broad, so this thesis focuses on the following five specific areas: - Prediction of connectivity of wireless devices. - Security intrusion detection, using network traffic information - Classification of network traffic, using the headers of the transmitted network packets - Estimation of the quality of the experience perceived by the user (QoE) when viewing multimedia streaming, using aggregate information of the network packets - Generation of synthetic traffic associated with security attacks and use of that synthetic traffic to improve security intrusion detection algorithms. The final intention is to create prediction and analysis models that produce improvements in the NTAP areas mentioned above. With this objective, this thesis provides advances in the application of machine learning techniques to the area of NTAP. These advances consist of: - Development of new machine learning models and architectures for NTAP - Define new ways to structure and transform training data so that existing machine learning models can be applied to specific NTAP problems. - Define algorithms for the creation of synthetic network traffic associated with specific events in the operation of the network (for example, specific types of intrusions), ensuring that the new synthetic data can be used as new training data. - Extension and application of classic models of machine learning to the area of NTAP, obtaining improvements in the classification or regression metrics and/or improvements in the performance measures of the algorithms (e.g. training time, prediction time, memory needs, ...).Departamento de Teoría de la Señal y Comunicaciones e Ingeniería TelemáticaDoctorado en Tecnologías de la Información y las Telecomunicacione