9 research outputs found

    Data Transmissions using Hub Nodes in Vehicular Social Networks

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    © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] Vehicular Social Networks (VSNs) consist of groups of individuals (i.e., people) who may share common interests, preferences and needs in the context of temporal spatial proximity on roads. In this environment, the impact of human social factors, such as mobility, willingness to cooperate and personal preferences, on vehicular connectivity is taken under consideration, thus extending the concept of Vehicular Ad-hoc Networks. In VSNs, vehicles are classified based on their social degree, a vehicle considered to be a ¿social¿ one if it accesses the vehicular social network and posts messages with a frequency higher than a given threshold. Therefore, to speed up the data dissemination process within a vehicular social network, a packet should be forwarded to those vehicles showing high social activity. In a previous paper, we introduced a new probabilistic-based broadcasting scheme called SCARF (SoCial-Aware Reliable Forwarding Technique for Vehicular Communications), and we analytically demonstrated its effectiveness in packet transmission reduction while guaranteeing network dissemination. In this paper, we assess SCARF in more realistic scenarios with real traffic traces, and we compare it with other similar techniques. We show that SCARF outperforms other approaches in terms of delivery ratio, while guaranteeing acceptable time delay values and average number of forwardings.Vegni, AM.; Souza, C.; Loscrí, V.; Hernández-Orallo, E.; Manzoni, P. (2020). Data Transmissions using Hub Nodes in Vehicular Social Networks. IEEE Transactions on Mobile Computing. 19(7):1570-1585. https://doi.org/10.1109/TMC.2019.2928803S1570158519

    Scheduling M2M traffic over LTE uplink of a dense small cell network

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    We present an approach to schedule Long Term Evolution (LTE) uplink (UL) Machine-to-Machine (M2M) traffic in a densely deployed heterogeneous network, over the street lights of a big boulevard for smart city applications. The small cells operate with frequency reuse 1, and inter-cell interference (ICI) is a critical issue to manage. We consider a 3rd Generation Partnership Project (3GPP) compliant scenario, where single-carrier frequency-division multiple access (SC-FDMA) is selected as the multiple access scheme, which requires that all resource blocks (RBs) allocated to a single user have to be contiguous in the frequency within each time slot. This adjacency constraint limits the flexibility of the frequency-domain packet scheduling (FDPS) and inter-cell interference coordination (ICIC), when trying to maximize the scheduling objectives, and this makes the problem NP-hard. We aim to solve a multi-objective optimization problem, to maximize the overall throughput, maximize the radio resource usage and minimize the ICI. This can be modelled through a mixed-integer linear programming (MILP) and solved through a heuristic implementable in the standards. We propose two models. The first one allocates resources based on the three optimization criteria, while the second model is more compact and is demonstrated through numerical evaluation in CPLEX, to be equivalent in the complexity, while it performs better and executes faster. We present simulation results in a 3GPP compliant network simulator, implementing the overall protocol stack, which support the effectiveness of our algorithm, for different M2M applications, with respect to the state-of-the-art approaches

    Contributions to Wireless multi-hop networks : Quality of Services and Security concerns

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    Ce document résume mes travaux de recherche conduits au cours de ces 6 dernières années. Le principal sujet de recherche de mes contributions est la conception et l’évaluation des solutions pour les réseaux sans fil multi-sauts en particulier les réseaux mobiles adhoc (MANETs), les réseaux véhiculaires ad hoc (VANETs), et les réseaux de capteurs sans fil (WSNs). La question clé de mes travaux de recherche est la suivante : « comment assurer un transport des données e cace en termes de qualité de services (QoS), de ressources énergétiques, et de sécurité dans les réseaux sans fil multi-sauts? » Pour répondre à cette question, j’ai travaillé en particulier sur les couches MAC et réseau et utilisé une approche inter-couches.Les réseaux sans fil multi-sauts présentent plusieurs problèmes liés à la gestion des ressources et au transport des données capable de supporter un grand nombre de nœuds, et d’assurer un haut niveau de qualité de service et de sécurité.Dans les réseaux MANETs, l’absence d’infrastructure ne permet pas d’utiliser l’approche centralisée pour gérer le partage des ressources, comme l’accès au canal.Contrairement au WLAN (réseau sans fil avec infrastructure), dans les réseaux Ad hoc les nœuds voisins deviennent concurrents et il est di cile d’assurer l’équité et l’optimisation du débit. La norme IEEE802.11 ne prend pas en compte l’équité entre les nœuds dans le contexte des MANETs. Bien que cette norme propose di érents niveaux de transmission, elle ne précise pas comment allouer ces débits de manière e cace. En outre, les MANETs sont basés sur le concept de la coopération entre les nœuds pour former et gérer un réseau. Le manque de coopération entre les nœuds signifie l’absence de tout le réseau. C’est pourquoi, il est primordial de trouver des solutions pour les nœuds non-coopératifs ou égoïstes. Enfin, la communication sans fil multi-sauts peut participer à l’augmentation de la couverture radio. Les nœuds de bordure doivent coopérer pour transmettre les paquets des nœuds voisins qui se trouvent en dehors de la zone de couverture de la station de base.Dans les réseaux VANETs, la dissémination des données pour les applications de sureté est un vrai défi. Pour assurer une distribution rapide et globale des informations, la méthode de transmission utilisée est la di usion. Cette méthode présente plusieurs inconvénients : perte massive des données due aux collisions, absence de confirmation de réception des paquets, non maîtrise du délai de transmission, et redondance de l’information. De plus, les applications de sureté transmettent des informations critiques, dont la fiabilité et l’authenticité doivent être assurées.Dans les réseaux WSNs, la limitation des ressources (bande passante, mémoire, énergie, et capacité de calcul), ainsi que le lien sans fil et la mobilité rendent la conception d’un protocole de communication e cace di cile. Certaines applications nécessitent un taux important de ressources (débit, énergie, etc) ainsi que des services de sécurité, comme la confidentialité et l’intégrité des données et l’authentification mutuelle. Ces paramètres sont opposés et leur conciliation est un véritable défi. De plus, pour transmettre de l’information, certaines applications ont besoin de connaître la position des nœuds dans le réseau. Les techniques de localisation sou rent d’un manque de précision en particulier dans un environnement fermé (indoor), et ne permettent pas de localiser les nœuds dans un intervalle de temps limité. Enfin, la localisation des nœuds est nécessaire pour assurer le suivi d’objet communicant ou non. Le suivi d’objet est un processus gourmand en énergie, et requiert de la précision.Pour répondre à ces défis, nous avons proposé et évalué des solutions, présentées de la manière suivante : l’ensemble des contributions dédiées aux réseaux MANETs est présenté dans le deuxième chapitre. Le troisième chapitre décrit les solutions apportées dans le cadre des réseaux VANETs. Enfin, les contributions liées aux réseaux WSNs sont présentées dans le quatrième chapitre

    Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks

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    This book presents collective works published in the recent Special Issue (SI) entitled "Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks”. These works expose the readership to the latest solutions and techniques for MANETs and VANETs. They cover interesting topics such as power-aware optimization solutions for MANETs, data dissemination in VANETs, adaptive multi-hop broadcast schemes for VANETs, multi-metric routing protocols for VANETs, and incentive mechanisms to encourage the distribution of information in VANETs. The book demonstrates pioneering work in these fields, investigates novel solutions and methods, and discusses future trends in these field

    Performance Evaluation of Smart Decision Support Systems on Healthcare

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    Medical activity requires responsibility not only from clinical knowledge and skill but also on the management of an enormous amount of information related to patient care. It is through proper treatment of information that experts can consistently build a healthy wellness policy. The primary objective for the development of decision support systems (DSSs) is to provide information to specialists when and where they are needed. These systems provide information, models, and data manipulation tools to help experts make better decisions in a variety of situations. Most of the challenges that smart DSSs face come from the great difficulty of dealing with large volumes of information, which is continuously generated by the most diverse types of devices and equipment, requiring high computational resources. This situation makes this type of system susceptible to not recovering information quickly for the decision making. As a result of this adversity, the information quality and the provision of an infrastructure capable of promoting the integration and articulation among different health information systems (HIS) become promising research topics in the field of electronic health (e-health) and that, for this same reason, are addressed in this research. The work described in this thesis is motivated by the need to propose novel approaches to deal with problems inherent to the acquisition, cleaning, integration, and aggregation of data obtained from different sources in e-health environments, as well as their analysis. To ensure the success of data integration and analysis in e-health environments, it is essential that machine-learning (ML) algorithms ensure system reliability. However, in this type of environment, it is not possible to guarantee a reliable scenario. This scenario makes intelligent SAD susceptible to predictive failures, which severely compromise overall system performance. On the other hand, systems can have their performance compromised due to the overload of information they can support. To solve some of these problems, this thesis presents several proposals and studies on the impact of ML algorithms in the monitoring and management of hypertensive disorders related to pregnancy of risk. The primary goals of the proposals presented in this thesis are to improve the overall performance of health information systems. In particular, ML-based methods are exploited to improve the prediction accuracy and optimize the use of monitoring device resources. It was demonstrated that the use of this type of strategy and methodology contributes to a significant increase in the performance of smart DSSs, not only concerning precision but also in the computational cost reduction used in the classification process. The observed results seek to contribute to the advance of state of the art in methods and strategies based on AI that aim to surpass some challenges that emerge from the integration and performance of the smart DSSs. With the use of algorithms based on AI, it is possible to quickly and automatically analyze a larger volume of complex data and focus on more accurate results, providing high-value predictions for a better decision making in real time and without human intervention.A atividade médica requer responsabilidade não apenas com base no conhecimento e na habilidade clínica, mas também na gestão de uma enorme quantidade de informações relacionadas ao atendimento ao paciente. É através do tratamento adequado das informações que os especialistas podem consistentemente construir uma política saudável de bem-estar. O principal objetivo para o desenvolvimento de sistemas de apoio à decisão (SAD) é fornecer informações aos especialistas onde e quando são necessárias. Esses sistemas fornecem informações, modelos e ferramentas de manipulação de dados para ajudar os especialistas a tomar melhores decisões em diversas situações. A maioria dos desafios que os SAD inteligentes enfrentam advêm da grande dificuldade de lidar com grandes volumes de dados, que é gerada constantemente pelos mais diversos tipos de dispositivos e equipamentos, exigindo elevados recursos computacionais. Essa situação torna este tipo de sistemas suscetível a não recuperar a informação rapidamente para a tomada de decisão. Como resultado dessa adversidade, a qualidade da informação e a provisão de uma infraestrutura capaz de promover a integração e a articulação entre diferentes sistemas de informação em saúde (SIS) tornam-se promissores tópicos de pesquisa no campo da saúde eletrônica (e-saúde) e que, por essa mesma razão, são abordadas nesta investigação. O trabalho descrito nesta tese é motivado pela necessidade de propor novas abordagens para lidar com os problemas inerentes à aquisição, limpeza, integração e agregação de dados obtidos de diferentes fontes em ambientes de e-saúde, bem como sua análise. Para garantir o sucesso da integração e análise de dados em ambientes e-saúde é importante que os algoritmos baseados em aprendizagem de máquina (AM) garantam a confiabilidade do sistema. No entanto, neste tipo de ambiente, não é possível garantir um cenário totalmente confiável. Esse cenário torna os SAD inteligentes suscetíveis à presença de falhas de predição que comprometem seriamente o desempenho geral do sistema. Por outro lado, os sistemas podem ter seu desempenho comprometido devido à sobrecarga de informações que podem suportar. Para tentar resolver alguns destes problemas, esta tese apresenta várias propostas e estudos sobre o impacto de algoritmos de AM na monitoria e gestão de transtornos hipertensivos relacionados com a gravidez (gestação) de risco. O objetivo das propostas apresentadas nesta tese é melhorar o desempenho global de sistemas de informação em saúde. Em particular, os métodos baseados em AM são explorados para melhorar a precisão da predição e otimizar o uso dos recursos dos dispositivos de monitorização. Ficou demonstrado que o uso deste tipo de estratégia e metodologia contribui para um aumento significativo do desempenho dos SAD inteligentes, não só em termos de precisão, mas também na diminuição do custo computacional utilizado no processo de classificação. Os resultados observados buscam contribuir para o avanço do estado da arte em métodos e estratégias baseadas em inteligência artificial que visam ultrapassar alguns desafios que advêm da integração e desempenho dos SAD inteligentes. Como o uso de algoritmos baseados em inteligência artificial é possível analisar de forma rápida e automática um volume maior de dados complexos e focar em resultados mais precisos, fornecendo previsões de alto valor para uma melhor tomada de decisão em tempo real e sem intervenção humana

    Diseño y desarrollo de una plataforma de comunicaciones descentralizada con WiFi Direct y protocolos M2M

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    El aumento del número de dispositivos IoT existentes hoy en día plantea enormes desafíos en los sistemas de comunicaciones. Para satisfacer las crecientes necesidades de los usuarios y utilizar eficientemente los escasos recursos disponibles, la comunicación Device-To-Device (D2D) se considera una importante tecnología emergente para el futuro de las redes. En este trabajo se propone un algoritmo de consenso anticipado y recurrente para la elección del mejor punto de acceso en caso de caída del nodo principal, cambios en la red e itinerancia. Se presenta el diseño y desarrollo de una plataforma de comunicaciones descentralizada que permita una comunicación eficiente y segura entre dispositivos sin necesidad de un concentrador o enrutador central, utilizando la tecnología WiFi Direct. Para este fin, se discuten las limitaciones actuales de los sistemas de comunicación centralizados tradicionales y los beneficios de los sistemas descentralizados, haciendo especial énfasis en los algoritmos de consenso. Más adelante, la investigación se centra en el diseño y la implementación de la plataforma propuesta, incluido el uso de WiFi Direct para el descubrimiento y la conexión de dispositivos, utilizando protocolos Machine-to-Machine (M2M) para una transferencia de datos eficiente, y se trata de solventar las limitaciones encontradas. Cabe destacar el uso de diferentes herramientas de simulación como WiDiSi o MQTTX para la obtención de unos resultados que nos hagan reafirmar las hipótesis planteadas a lo largo de esta investigación. Por último, analizando los resultados, dado que la mayoría de los estudios se basan en la aleatoriedad para la selección del líder, se propone el diseño de un algoritmo de consenso basado en el algoritmo Raft que permita establecer criterios más útiles para conseguir una mejora de calidad en torno a la elección, en el contexto de WiFi Direct finalizando con la presentación de los resultados que muestran como la flexibilidad inherente del algoritmo proporciona una solución adaptable a diversas aplicaciones y escenarios en sistemas distribuidos abriendo nuevas posibilidades para investigaciones futuras y desarrollos en el campo de las redes distribuidas.The increase in the number of existing IoT devices today poses enormous challenges in communication systems. To meet the growing needs of users and efficiently use scarce resources, Device-To-Device (D2D) communication is considered an important emerging technology for the future of networks. In this work, an advanced and recurring consensus algorithm is proposed for selecting the best access point in case of main node failure, network changes, and roaming. The design and development of a decentralized communication platform is presented, enabling efficient and secure communication between devices without the need for a central hub or router, using WiFi Direct technology. To this end, the current limitations of traditional centralized communication systems are discussed, along with the benefits of decentralized systems, with a special emphasis on consensus algorithms. Subsequently, the research focuses on the design and implementation of the proposed platform, including the use of WiFi Direct for device discovery and connection, using Machineto- Machine (M2M) protocols for efficient data transfer, and addressing the encountered limitations. It is worth noting the application of different simulation tools such as WiDiSi or MQTTX to obtain preliminary results that support the hypotheses raised throughout this research. Finally, considering the results, given that the majority of studies rely on randomness for leader selection, the design of a consensus algorithm based on Raft algorithm is proposed in the context of WiFi Direct in order to establish more useful criteria for achieving an improvement in quality regarding the selection. This culminates in the presentation of results demonstrating how the inherent flexibility of the algorithm provides an adaptable solution for various applications and scenarios in distributed systems, thereby opening up new possibilities for future research and developments in the field of distributed networks.Universidad de Sevilla. Grado en Ingeniería de las Tecnologías de Telecomunicació

    State of the Art and Future Perspectives in Smart and Sustainable Urban Development

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    This book contributes to the conceptual and practical knowledge pools in order to improve the research and practice on smart and sustainable urban development by presenting an informed understanding of the subject to scholars, policymakers, and practitioners. This book presents contributions—in the form of research articles, literature reviews, case reports, and short communications—offering insights into the smart and sustainable urban development by conducting in-depth conceptual debates, detailed case study descriptions, thorough empirical investigations, systematic literature reviews, or forecasting analyses. This way, the book forms a repository of relevant information, material, and knowledge to support research, policymaking, practice, and the transferability of experiences to address urbanization and other planetary challenges
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