2,575 research outputs found

    Pervasive intelligent routing in content centric delay tolerant networks

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    This paper introduces a Swarm-Intelligence based Routing protocol (SIR) that aims to efficiently route information in content centric Delay Tolerant Networks (CCDTN) also dubbed pocket switched networks. First, this paper formalizes the notion of optimal path in CCDTN and introduces an original and efficient algorithm to process these paths in dynamic graphs. The properties and some invariant features of these optimal paths are analyzed and derived from several real traces. Then, this paper shows how optimal path in CCDTN can be found and used from a fully distributed swarm-intelligence based approach of which the global intelligent behavior (i.e. shortest path discovery and use) emerges from simple peer to peer interactions applied during opportunistic contacts. This leads to the definition of the SIR routing protocol of which the consistency, efficiency and performances are demonstrated from intensive representative simulations

    Impacto de mobilidade em encaminhamento centrado no utilizador

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    Doutoramento em Engenharia Eletrotécnica -TelecomunicaçõesRecent paradigms in wireless communication architectures describe environments where nodes present a highly dynamic behavior (e.g., User Centric Networks). In such environments, routing is still performed based on the regular packet-switched behavior of store-and-forward. Albeit sufficient to compute at least an adequate path between a source and a destination, such routing behavior cannot adequately sustain the highly nomadic lifestyle that Internet users are today experiencing. This thesis aims to analyse the impact of the nodes’ mobility on routing scenarios. It also aims at the development of forwarding concepts that help in message forwarding across graphs where nodes exhibit human mobility patterns, as is the case of most of the user-centric wireless networks today. The first part of the work involved the analysis of the mobility impact on routing, and we found that node mobility significance can affect routing performance, and it depends on the link length, distance, and mobility patterns of nodes. The study of current mobility parameters showed that they capture mobility partially. The routing protocol robustness to node mobility depends on the routing metric sensitivity to node mobility. As such, mobility-aware routing metrics were devised to increase routing robustness to node mobility. Two categories of routing metrics proposed are the time-based and spatial correlation-based. For the validation of the metrics, several mobility models were used, which include the ones that mimic human mobility patterns. The metrics were implemented using the Network Simulator tool using two widely used multi-hop routing protocols of Optimized Link State Routing (OLSR) and Ad hoc On Demand Distance Vector (AODV). Using the proposed metrics, we reduced the path re-computation frequency compared to the benchmark metric. This means that more stable nodes were used to route data. The time-based routing metrics generally performed well across the different node mobility scenarios used. We also noted a variation on the performance of the metrics, including the benchmark metric, under different mobility models, due to the differences in the node mobility governing rules of the models.Os paradigmas recentes de arquiteturas de comunicação sem fios consistem em ambientes onde os dispositivos apresentam um comportamento dinâmico (e.g., Redes Centradas no Utilizador). Nestes ambientes, o encaminhamento de dados ainda é realizado com base no comportamento de armazenamento e encaminhamento da comutação clássica de pacotes. Embora seja suficiente para calcular, pelo menos, um caminho adequado entre uma origem e um destino, tal comportamento de encaminhamento não é adequado nas redes móveis e sem fios atuais. Esta tese tem como objetivo analisar o impacto da mobilidade dos utilizadores sobre os diferentes cenários de encaminhamento. A tese também visa o desenvolvimento de conceitos de encaminhamento que ajudam na distribuição de dados através de grafos, nos quais os vértices exibem padrões de mobilidade humana, como é o caso hoje em dia para a maior parte das redes sem fios centradas no utilizador. A primeira parte desta tese envolveu a análise do impacto da mobilidade dos utilizadores no encaminhamento, com a análise de que a mobilidade, para afetar o desempenho do encaminhamento, depende do comprimento do caminho entre a origem e o destino, da distância entre os dispositivos, e dos diferentes padrões de mobilidade. O estudo dos atuais parâmetros de mobilidade mostrou que eles capturam parcialmente a mobilidade dos utilizadores. A robustez dos protocolos de encaminhamento depende da sensibilidade das métricas no que concerne a esta mobilidade. Assim, foram concebidas métricas de encaminhamento baseadas na mobilidade dos utilizadores para aumentar a robustez do encaminhamento em relação à mobilidade. As duas categorias de métricas de encaminhamento criadas foram métricas que têm como base o tempo e a correlação espacial. Para a validação das métricas foram utilizados vários modelos de mobilidade, incluindo os modelos que imitam padrões de mobilidade humana. As métricas foram implementadas utilizando a ferramenta Network Simulator e considerando dois protocolos de encaminhamento por múltiplos saltos amplamente utilizados, o Optimized Link State Routing (OLSR) e o Adhoc On Demand Distance Vector (AODV). Com a utilização das métricas propostas observa-se que a frequência de realização de novos cálculos de caminhos de comunicação foi reduzida em relação à métrica de referência. Isto significa que foram usados caminhos mais estáveis para encaminhar dados. As métricas de encaminhamento baseadas no tempo apresentam geralmente um bom desempenho nos diferentes cenários de mobilidade utilizados. Observou-se também uma variação no desempenho das métricas, incluindo a métrica de referência, nos diferentes modelos de mobilidade considerados, devido a diferenças nas regras de mobilidade dos utilizadores dos diferentes modelos

    Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

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    Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

    An approach to pervasive monitoring in dynamic learning contexts : data sensing, communication support and awareness provision

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    It is within the capabilities of current technology to support the emerging learning paradigms. These paradigms suggest that today’s learning activities and environments are pervas ive and require a higher level of dynamism than the traditional learning contexts. Therefore, we have to rethink our approach to learning and use technology not only as a digital information support, but also as an instrument to reinforce knowledge, foster collaboration, promote creativity and provide richer learning experiences. Particularly, this thesis was motivated by the rapidly growing number of smartphone users and the fact that these devices are increasingly becoming more and more resource-rich, in terms of their communication and sensing technologies, display capabilities battery autonomy, etc. Hence, this dissertation benefits from the ubiquity and development of mobile technology, aiming to bridge the gap between the challenges posed by modern learning requirements and the capabilities of current technology. The sensors embedded in smartphones can be used to capture diverse behavioural and social aspects of the users. For example, using microphone and Bluetooth is possible to identify conversation patterns, discover users in proximity and detect face-to-face meetings. This fact opens up exciting possibilities to monitor the behaviour of the user and to provide meaningful feedback. This feedback offers useful information that can help people be aware of and reflect on their behaviour and its effects, and take the necessary actions to improve them. Consequently, we propose a pervasive monitoring system that take advantage of the capabilities of modern smartphones, us ing them to s upport the awarenes s provis ion about as pects of the activities that take place in today’s pervas ive learning environments. This pervasive monitoring system provides (i) an autonomous sensing platform to capture complex information about processes and interactions that take place across multiple learning environments, (ii) an on-demand and s elf-m anaged communication infras tructure, and (ii) a dis play facility to provide “awarenes s inform ation” to the s tudents and/or lecturers. For the proposed system, we followed a research approach that have three main components. First, the description of a generalized framework for pervasive sensing that enables collaborative sensing interactions between smartphones and other types of devices. By allowing complex data capture interactions with diverse remote sensors, devices and data sources, this framework allows to improve the information quality while saving energy in the local device. Second, the evaluation, through a real-world deployment, of the suitability of ad hoc networks to support the diverse communication processes required for pervasive monitoring. This component also includes a method to improve the scalability and reduce the costs of these networks. Third, the design of two awareness mechanisms to allow flexible provision of information in dynamic and heterogeneous learning contexts. These mechanisms rely on the use of smartphones as adaptable devices that can be used directly as awareness displays or as communication bridges to enable interaction with other remote displays available in the environment. Diverse aspects of the proposed system were evaluated through a number of simulations, real-world experiments, user studies and prototype evaluations. The experimental evaluation of the data capture and communication aspects of the system provided empirical evidence of the usefulness and suitability of the proposed approach to support the development of pervasive monitoring solutions. In addition, the proof-of-concept deployments of the proposed awareness mechanisms, performed in both laboratory and real-world learning environments, provided quantitative and qualitative indicators that such mechanisms improve the quality of the awareness information and the user experienceLa tecnología moderna tiene capacidad de dar apoyo a los paradigmas de aprendizaje emergentes. Estos paradigmas sugieren que las actividades de aprendizaje actuales, caracterizadas por la ubicuidad de entornos, son más dinámicas y complejas que los contextos de aprendizaje tradicionales. Por tanto, tenemos que reformular nuestro acercamiento al aprendizaje, consiguiendo que la tecnología sirva no solo como mero soporte de información, sino como medio para reforzar el conocimiento, fomentar la colaboración, estimular la creatividad y proporcionar experiencias de aprendizaje enriquecedoras. Esta tesis doctoral está motivada por el vertiginoso crecimiento de usuarios de smartphones y el hecho de que estos son cada vez más potentes en cuanto a tecnologías de comunicación, sensores, displays, autonomía energética, etc. Por tanto, esta tesis aprovecha la ubicuidad y el desarrollo de esta tecnología, con el objetivo de reducir la brecha entre los desafíos del aprendizaje moderno y las capacidades de la tecnología actual. Los sensores integrados en los smartphones pueden ser utilizados para reconocer diversos aspectos del comportamiento individual y social de los usuarios. Por ejemplo, a través del micrófono y el Bluetooth, es posible determinar patrones de conversación, encontrar usuarios cercanos y detectar reuniones presenciales. Este hecho abre un interesante abanico de posibilidades, pudiendo monitorizar aspectos del comportamiento del usuario y proveer un feedback significativo. Dicho feedback, puede ayudar a los usuarios a reflexionar sobre su comportamiento y los efectos que provoca, con el fin de tomar medidas necesarias para mejorarlo. Proponemos un sistema de monitorización generalizado que aproveche las capacidades de los smartphones para proporcionar información a los usuarios, ayudándolos a percibir y tomar conciencia sobre diversos aspectos de las actividades que se desarrollan en contextos de aprendizaje modernos. Este sistema ofrece: (i) una plataforma de detección autónoma, que captura información compleja sobre los procesos e interacciones de aprendizaje; (ii) una infraestructura de comunicación autogestionable y; (iii) un servicio de visualización que provee “información de percepción” a estudiantes y/o profesores. Para la elaboración de este sistema nos hemos centrado en tres áreas de investigación. Primero, la descripción de una infraestructura de detección generalizada, que facilita interacciones entre smartphones y otros dispositivos. Al permitir interacciones complejas para la captura de datos entre diversos sensores, dispositivos y fuentes de datos remotos, esta infraestructura consigue mejorar la calidad de la información y ahorrar energía en el dispositivo local. Segundo, la evaluación, a través de pruebas reales, de la idoneidad de las redes ad hoc como apoyo de los diversos procesos de comunicación requeridos en la monitorización generalizada. Este área incluye un método que incrementa la escalabilidad y reduce el coste de estas redes. Tercero, el diseño de dos mecanismos de percepción que permiten la provisión flexible de información en contextos de aprendizaje dinámicos y heterogéneos. Estos mecanismos descansan en la versatilidad de los smartphones, que pueden ser utilizados directamente como displays de percepción o como puentes de comunicación que habilitan la interacción con otros displays remotos del entorno. Diferentes aspectos del sistema propuesto han sido evaluados a través de simulaciones, experimentos reales, estudios de usuarios y evaluaciones de prototipos. La evaluación experimental proporcionó evidencia empírica de la idoneidad del sistema para apoyar el desarrollo de soluciones de monitorización generalizadas. Además, las pruebas de concepto realizadas tanto en entornos de aprendizajes reales como en el laboratorio, aportaron indicadores cuantitativos y cualitativos de que estos mecanismos mejoran la calidad de la información de percepción y la experiencia del usuario.Postprint (published version

    Offloading Content with Self-organizing Mobile Fogs

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    Mobile users in an urban environment access content on the internet from different locations. It is challenging for the current service providers to cope with the increasing content demand from a large number of collocated mobile users. In-network caching to offload content at nodes closer to users alleviate the issue, though efficient cache management is required to find out who should cache what, when and where in an urban environment, given nodes limited computing, communication and caching resources. To address this, we first define a novel relation between content popularity and availability in the network and investigate a node's eligibility to cache content based on its urban reachability. We then allow nodes to self-organize into mobile fogs to increase the distributed cache and maximize content availability in a cost-effective manner. However, to cater rational nodes, we propose a coalition game for the nodes to offer a maximum "virtual cache" assuming a monetary reward is paid to them by the service/content provider. Nodes are allowed to merge into different spatio-temporal coalitions in order to increase the distributed cache size at the network edge. Results obtained through simulations using realistic urban mobility trace validate the performance of our caching system showing a ratio of 60-85% of cache hits compared to the 30-40% obtained by the existing schemes and 10% in case of no coalition

    Efficient Hash-routing and Domain Clustering Techniques for Information-Centric Networks

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    Hash-routing is a well-known technique used in server-cluster environments to direct content requests to the responsible servers hosting the requested content. In this work, we look at hash-routing from a different angle and apply the technique to Information-Centric Networking (ICN) environments, where in-network content caches serve as temporary storage for content. In particular, edge-domain routers re-direct requests to in-network caches, more often than not off the shortest path, according to the hash-assignment function. Although the benefits of this off-path in-network caching scheme are significant (e.g., high cache hit rate with minimal co-ordination overhead), the basic scheme comes with disadvantages. That is, in case of very large domains the off-path detour of requests might increase latency to prohibitive levels. In order to deal with extensive detour delays, we investigate nodal/domain clustering techniques, according to which large domains are split in clusters, which in turn apply hash-routing in the subset of nodes of each cluster. We model and evaluate the behaviour of nodal clustering and report significant improvement in delivery latency, which comes at the cost of a slight decrease in cache hit rates (i.e., up to 50% improvement in delivery latency for less than 10% decrease in cache hit rate compared to the original hash-routing scheme applied in the whole domain)

    Understanding information centric layer of adaptive collaborative caching framework in mobile disconnection-prone networks

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    Smart networks and services leverage in-network caching to improve transmission efficiency and support large amount of content sharing, decrease high operating costs and handle disconnections. In this paper, we investigate the complex challenges related to content popularity weighting process in collaborative caching algorithm in heterogeneous mobile disconnection prone environments. We describe a reputation-based popularity weighting mechanism built in information-centric layer of our adaptive collaborative caching framework CafRepCache which considers a realistic case where caching points gathering content popularity observed by nodes differentiates between them according to node's reputation and network's connectivity. We extensively evaluate CafRepCache with competitive protocols across three heterogeneous real-world mobility, connectivity traces and use YouTube dataset for different workload and content popularity patterns. We show that our collaborative caching mechanism CafRepCache balances the trade-off that achieves higher cache hit ratio, efficiency and success ratios while keeping lower delays, packet loss and caching footprint compared to competing protocols across three traces in the face of dynamic mobility of publishers and subscribers
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