108 research outputs found

    Ubiquitous Computing for Remote Cardiac Patient Monitoring: A Survey

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    New wireless technologies, such as wireless LAN and sensor networks, for telecardiology purposes give new possibilities for monitoring vital parameters with wearable biomedical sensors, and give patients the freedom to be mobile and still be under continuous monitoring and thereby better quality of patient care. This paper will detail the architecture and quality-of-service (QoS) characteristics in integrated wireless telecardiology platforms. It will also discuss the current promising hardware/software platforms for wireless cardiac monitoring. The design methodology and challenges are provided for realistic implementation

    Models and Protocols for Resource Optimization in Wireless Mesh Networks

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    Wireless mesh networks are built on a mix of fixed and mobile nodes interconnected via wireless links to form a multihop ad hoc network. An emerging application area for wireless mesh networks is their evolution into a converged infrastructure used to share and extend, to mobile users, the wireless Internet connectivity of sparsely deployed fixed lines with heterogeneous capacity, ranging from ISP-owned broadband links to subscriber owned low-speed connections. In this thesis we address different key research issues for this networking scenario. First, we propose an analytical predictive tool, developing a queuing network model capable of predicting the network capacity and we use it in a load aware routing protocol in order to provide, to the end users, a quality of service based on the throughput. We then extend the queuing network model and introduce a multi-class queuing network model to predict analytically the average end-to-end packet delay of the traffic flows among the mobile end users and the Internet. The analytical models are validated against simulation. Second, we propose an address auto-configuration solution to extend the coverage of a wireless mesh network by interconnecting it to a mobile ad hoc network in a transparent way for the infrastructure network (i.e., the legacy Internet interconnected to the wireless mesh network). Third, we implement two real testbed prototypes of the proposed solutions as a proof-of-concept, both for the load aware routing protocol and the auto-configuration protocol. Finally we discuss the issues related to the adoption of ad hoc networking technologies to address the fragility of our communication infrastructure and to build the next generation of dependable, secure and rapidly deployable communications infrastructures

    Connectivity Optimization in Robotic Networks

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    La collaboration entre multiple appareils électroniques (e.g. smartphones, ordinateurs, robots, senseurs et routeurs) est une tendance qui suscite un vif intérêt tant ses applications semblent prometteuses. Les maisons autonomes ou villes intelligentes figurent parmi la prodigieuse variété d’exemples. La communication entre appareils est une des clés du succès de leur coopération. Sans un bon système de communication, les appareils se retrouvent vite incapables d’échanger l’information nécessaire à la prise de décision. Pour garantir une bonne communication, il faut un réseau solide sur lequel elle puisse reposer. Nous pourrions envisager une organisation centralisée, puisqu’elles sont si répandues. Nos téléphones portables communiquent grâce à des antennes-relais ; et nous naviguons sur l’internet grâce à des routeurs. Dans un réseau centralisé, si un noeud principal, tel qu’une antenne ou un routeur, est défaillant, la capacité à communiquer en est dramatiquement diminuée. Or, certaines collaborations entre appareils interviennent, parfois, dans des situations où les infrastructures classiques ne sont pas accessibles. C’est le cas pour les opérations de sauvetages, où les moyens de communications classiques ont pu être endommagés à la suite d’un sinistre. D’autres organisations sont alors plus judicieuses. Dans les réseaux ad hoc, par exemple, il n’existe pas de noeud central, car chaque appareil peut servir au transit de l’information. Cette dissertation s’intéresse à la mise en place de réseaux ad hoc et mobiles entre smartphones et drones. Elle s’inscrit dans le cadre d’un partenariat, entre Humanitas Solutions et l’École Polytechnique de Montréal, qui vise à établir un moyen de communication basé sur ces appareils, pour connecter victimes et premiers secours lors d’opérations de sauvetages. Pour mener à bien ce projet, nous devons permettre aux appareils électroniques de communiquer sans recourir à quelconque infrastructure. Pour relayer l’information, nous devons également maintenir les drones connectés au-dessus de la zone sinistrée.----------ABSTRACT: Because of their promising applications, the interest for machine-to-machine interaction has soared (e.g. between smartphones, laptops, robots, sensors, or routers). Autonomous homes and smart cities are just two examples among the many. Without a good communication system, devices are unable to share relevant information and take effective decisions. Thus, inter-device communication is key for successful cooperations. To guarantee suitable communication, devices need to rely on a robust network. One might think of classical centralized network architecture since it is so common – antennae relay our smartphone communications, and routers provide us with an Internet connection at home. However, this architecture is not adequate for every application. When a central node (e.g. an antenna or a router) fails, it can cripple all the network. Moreover, fixed infrastructure is not always available, which is detrimental for applications like search and rescue operations. Hence, other network designs can be more suitable, like ad hoc networks, where there is no central node and every device can route information. This work aims at establishing mobile ad hoc networks between multiple devices for search and rescue operations. This thesis is framed by a partnership between Humanitas Solutions and École Polytechnique de Montréal, whose goal is to relay information between victims and first responders by the use of smartphones and flying robots (i.e. drones). For this purpose, we have to enable infrastructureless communications between devices and maintain drones connected over the disaster area

    Design and evaluation of wireless dense networks : application to in-flight entertainment systems

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    Le réseau sans fil est l'un des domaines de réseautage les plus prometteurs avec des caractéristiques uniques qui peuvent fournir la connectivité dans les situations où il est difficile d'utiliser un réseau filaire, ou lorsque la mobilité des nœuds est nécessaire. Cependant, le milieu de travail impose généralement diverses contraintes, où les appareils sans fil font face à différents défis lors du partage des moyens de communication. De plus, le problème s'aggrave avec l'augmentation du nombre de nœuds. Différentes solutions ont été introduites pour faire face aux réseaux très denses. D'autre part, un nœud avec une densité très faible peut créer un problème de connectivité et peut conduire à l'optension de nœuds isolés et non connectes au réseau. La densité d'un réseau est définit en fonction du nombre de nœuds voisins directs au sein de la portée de transmission du nœud. Cependant, nous croyons que ces métriques ne sont pas suffisants et nous proposons une nouvelle mesure qui considère le nombre de voisins directs et la performance du réseau. Ainsi, la réponse du réseau, respectant l'augmentation du nombre de nœuds, est considérée lors du choix du niveau de la densité. Nous avons défini deux termes: l'auto-organisation et l'auto-configuration, qui sont généralement utilisés de façon interchangeable dans la littérature en mettant en relief la différence entre eux. Nous estimons qu'une définition claire de la terminologie peut éliminer beaucoup d'ambiguïté et aider à présenter les concepts de recherche plus clairement. Certaines applications, telles que Ies systèmes "In-Flight Entertainment (IFE)" qui se trouvent à l'intérieur des cabines d'avions, peuveut être considérées comme des systèmes sans fil de haute densité, même si peu de nœuds sont relativement présents. Pour résoudre ce problème, nous proposons une architecture hétérogène de différentes technologies à fin de surmonter les contraintes spécifiques de l'intérieur de la cabine. Chaque technologie vise à résoudre une partie du problème. Nous avons réalisé diverses expérimentations et simulations pour montrer la faisabilité de l'architecture proposée. Nous avons introduit un nouveau protocole d'auto-organisation qui utilise des antennes intelligentes pour aider certains composants du système IFE; à savoir les unités d'affichage et leurs systèmes de commande, à s'identifier les uns les autres sans aucune configuration préliminaire. Le protocole a été conçu et vérifié en utilisant le langage UML, puis, un module de NS2 a été créé pour tester les différents scénarios.Wireless networking is one of the most challenging networking domains with unique features that can provide connectivity in situations where it is difficult to use wired networking, or when ! node mobility is required. However, the working environment us! ually im poses various constrains, where wireless devices face various challenges when sharing the communication media. Furthermore, the problem becomes worse when the number of nodes increase. Different solutions were introduced to cope with highly dense networks. On the other hand, a very low density can create a poor connectivity problem and may lead to have isolated nodes with no connection to the network. It is common to define network density according to the number of direct neighboring nodes within the node transmission range. However, we believe that such metric is not enough. Thus, we propose a new metric that encompasses the number of direct neighbors and the network performance. In this way, the network response, due to the increasing number of nodes, is considered when deciding the density level. Moreover, we defined two terms, self-organization and self-configuration, which are usually used interchangeably in the literature through highlighting the difference ! between them. We believe that having a clear definition for terminology can eliminate a lot of ambiguity and help to present the research concepts more clearly. Some applications, such as In-Flight Entertainment (IFE) systems inside the aircraft cabin, can be considered as wirelessly high dense even if relatively few nodes are present. To solve this problem, we propose a heterogeneous architecture of different technologies to overcome the inherited constrains inside the cabin. Each technology aims at solving a part of the problem. We held various experimentation and simulations to show the feasibility of the proposed architecture

    Enabling Secure Direct Connectivity Under Intermittent Cellular Network Assistance

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    This work targets at investigating direct communications as a promising technology for the next-generation 5G wireless ecosystem that improves the degrees of spatial reuse and creates new opportunities for users in proximity. While direct connectivity has originally emerged as a technology enabler for public safety services, it is likely to remain in the heart of the 5G ecosystem by spawning a wide diversity of proximate applications and services. Direct communications couples together the centralized and the distributed network architectures, and as such requires respective enablers for secure, private, and trusted data exchange especially when cellular control link is not available at all times. Within the research group, the author was tasked to provide the state-of-the-art technology overview and to propose a novel algorithm for maintaining security functions of proximate devices in case of unreliable cellular connectivity, whenever a new device joins the secure group of users or an existing device leaves it. The proposed solution and its rigorous practical implementation detailed in this work open door to a new generation of secure proximity-based services and applications in future wireless communications systems

    Mission-based mobility models for UAV networks

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    Las redes UAV han atraído la atención de los investigadores durante la última década. Las numerosas posibilidades que ofrecen los sistemas single-UAV aumentan considerablemente al usar múltiples UAV. Sin embargo, el gran potencial del sistema multi-UAV viene con un precio: la complejidad de controlar todos los aspectos necesarios para garantizar que los UAVs cumplen la misión que se les ha asignado. Ha habido numerosas investigaciones dedicadas a los sistemas multi-UAV en el campo de la robótica en las cuales se han utilizado grupos de UAVs para diferentes aplicaciones. Sin embargo, los aspectos relacionados con la red que forman estos sistemas han comenzado a reclamar un lugar entre la comunidad de investigación y han hecho que las redes de UAVs se consideren como un nuevo paradigma entre las redes multi-salto. La investigación de redes de UAVs, de manera similar a otras redes multi-salto, se divide principalmente en dos categorías: i) modelos de movilidad que capturan la movilidad de la red, y ii) algoritmos de enrutamiento. Ambas categorías han heredado muchos algoritmos que pertenecían a las redes MANET, que fueron el primer paradigma de redes multi-salto que atrajo la atención de los investigadores. Aunque hay esfuerzos de investigación en curso que proponen soluciones para ambas categorías, el número de modelos de movilidad y algoritmos de enrutamiento específicos para redes UAV es limitado. Además, en el caso de los modelos de movilidad, las soluciones existentes propuestas son simplistas y apenas representan la movilidad real de un equipo de UAVs, los cuales se utilizan principalmente en operaciones orientadas a misiones, en la que cada UAV tiene asignados movimientos específicos. Esta tesis propone dos modelos de movilidad basados en misiones para una red de UAVs que realiza dos operaciones diferentes. El escenario elegido en el que se desarrollan las misiones corresponde con una región en la que ha ocurrido, por ejemplo, un desastre natural. La elección de este tipo de escenario se debe a que en zonas de desastre, la infraestructura de comunicaciones comúnmente está dañada o totalmente destruida. En este tipo de situaciones, una red de UAVs ofrece la posibilidad de desplegar rápidamente una red de comunicaciones. El primer modelo de movilidad, llamado dPSO-U, ha sido diseñado para capturar la movilidad de una red UAV en una misión con dos objetivos principales: i) explorar el área del escenario para descubrir las ubicaciones de los nodos terrestres, y ii) hacer que los UAVs converjan de manera autónoma a los grupos en los que se organizan los nodos terrestres (también conocidos como clusters). El modelo de movilidad dPSO-U se basa en el conocido algoritmo particle swarm optimization (PSO), considerando los UAV como las partículas del algoritmo, y también utilizando el concepto de valores dinámicos para la inercia, el local best y el neighbour best de manera que el modelo de movilidad tenga ambas capacidades: la de exploración y la de convergencia. El segundo modelo, denominado modelo de movilidad Jaccard-based, captura la movilidad de una red UAV que tiene asignada la misión de proporcionar servicios de comunicación inalámbrica en un escenario de mediano tamaño. En este modelo de movilidad se ha utilizado una combinación del virtual forces algorithm (VFA), de la distancia Jaccard entre cada par de UAVs y metaheurísticas como hill climbing y simulated annealing, para cumplir los dos objetivos de la misión: i) maximizar el número de nodos terrestres (víctimas) que se encuentran bajo el área de cobertura inalámbrica de la red UAV, y ii) mantener la red UAV como una red conectada, es decir, evitando las desconexiones entre UAV. Se han realizado simulaciones exhaustivas con herramientas software específicamente desarrolladas para los modelos de movilidad propuestos. También se ha definido un conjunto de métricas para cada modelo de movilidad. Estas métricas se han utilizado para validar la capacidad de los modelos de movilidad propuestos de emular los movimientos de una red UAV en cada misión.UAV networks have attracted the attention of the research community in the last decade. The numerous capabilities of single-UAV systems increase considerably by using multiple UAVs. The great potential of a multi-UAV system comes with a price though: the complexity of controlling all the aspects required to guarantee that the UAV team accomplish the mission that it has been assigned. There have been numerous research works devoted to multi-UAV systems in the field of robotics using UAV teams for different applications. However, the networking aspects of multi-UAV systems started to claim a place among the research community and have made UAV networks to be considered as a new paradigm among the multihop ad hoc networks. UAV networks research, in a similar manner to other multihop ad hoc networks, is mainly divided into two categories: i) mobility models that capture the network mobility, and ii) routing algorithms. Both categories have inherited previous algorithms mechanisms that originally belong to MANETs, being these the first multihop networking paradigm attracting the attention of researchers. Although there are ongoing research efforts proposing solutions for the aforementioned categories, the number of UAV networks-specific mobility models and routing algorithms is limited. In addition, in the case of the mobility models, the existing solutions proposed are simplistic and barely represent the real mobility of a UAV team, which are mainly used in missions-oriented operations. This thesis proposes two mission-based mobility models for a UAV network carrying out two different operations over a disaster-like scenario. The reason for selecting a disaster scenario is because, usually, the common communication infrastructure is malfunctioning or completely destroyed. In these cases, a UAV network allows building a support communication network which is rapidly deployed. The first mobility model, called dPSO-U, has been designed for capturing the mobility of a UAV network in a mission with two main objectives: i) exploring the scenario area for discovering the location of ground nodes, and ii) making the UAVs to autonomously converge to the groups in which the nodes are organized (also referred to as clusters). The dPSO-U mobility model is based on the well-known particle swarm optimization algorithm (PSO), considering the UAVs as the particles of the algorithm, and also using the concept of dynamic inertia, local best and neighbour best weights so the mobility model can have both abilities: exploration and convergence. The second one, called Jaccard-based mobility model, captures the mobility of a UAV network that has been assigned with the mission of providing wireless communication services in a medium-scale scenario. A combination of the virtual forces algorithm (VFA), the Jaccard distance between each pair of UAVs and metaheuristics such as hill climbing or simulated annealing have been used in this mobility model in order to meet the two mission objectives: i) to maximize the number of ground nodes (i.e. victims) under the UAV network wireless coverage area, and ii) to maintain the UAV network as a connected network, i.e. avoiding UAV disconnections. Extensive simulations have been performed with software tools that have been specifically developed for the proposed mobility models. Also, a set of metrics have been defined and measured for each mobility model. These metrics have been used for validating the ability of the proposed mobility models to emulate the movements of a UAV network in each mission

    Is There Light at the Ends of the Tunnel? Wireless Sensor Networks for Adaptive Lighting in Road Tunnels

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    Existing deployments of wireless sensor networks (WSNs) are often conceived as stand-alone monitoring tools. In this paper, we report instead on a deployment where the WSN is a key component of a closed-loop control system for adaptive lighting in operational road tunnels. WSN nodes along the tunnel walls report light readings to a control station, which closes the loop by setting the intensity of lamps to match a legislated curve. The ability to match dynamically the lighting levels to the actual environmental conditions improves the tunnel safety and reduces its power consumption. The use of WSNs in a closed-loop system, combined with the real-world, harsh setting of operational road tunnels, induces tighter requirements on the quality and timeliness of sensed data, as well as on the reliability and lifetime of the network. In this work, we test to what extent mainstream WSN technology meets these challenges, using a dedicated design that however relies on wellestablished techniques. The paper describes the hw/sw architecture we devised by focusing on the WSN component, and analyzes its performance through experiments in a real, operational tunnel

    From MANET to people-centric networking: Milestones and open research challenges

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    In this paper, we discuss the state of the art of (mobile) multi-hop ad hoc networking with the aim to present the current status of the research activities and identify the consolidated research areas, with limited research opportunities, and the hot and emerging research areas for which further research is required. We start by briefly discussing the MANET paradigm, and why the research on MANET protocols is now a cold research topic. Then we analyze the active research areas. Specifically, after discussing the wireless-network technologies, we analyze four successful ad hoc networking paradigms, mesh networks, opportunistic networks, vehicular networks, and sensor networks that emerged from the MANET world. We also present an emerging research direction in the multi-hop ad hoc networking field: people centric networking, triggered by the increasing penetration of the smartphones in everyday life, which is generating a people-centric revolution in computing and communications

    On-the-Fly Establishment of Multi-hop D2D Communication based on Android Smartphones and Embedded Platforms: Implementation and Real-Life Experiments

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    Masteroppgave informasjons- og kommunikasjonsteknologi - Universitetet i Agder, 2015(Konfidensiell til/confidential until 01.07.2020
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