75 research outputs found

    Communication Algorithms for Wireless Ad Hoc Networks

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    In this dissertation we present deterministic algorithms for reliable and efficient communication in ad hoc networks. In the first part of this dissertation we give a specification for a reliable neighbor discovery layer for mobile ad hoc networks. We present two different algorithms that implement this layer with varying progress guarantees. In the second part of this dissertation we give an algorithm which allows nodes in a mobile wireless ad hoc network to communicate reliably and at the same time maintain local neighborhood information. In the last part of this dissertation we look at the distributed trigger counting problem in the wireless ad hoc network setting. We present a deterministic algorithm for this problem which is communication efficient in terms of the the maximum number of messages received by any processor in the system

    Satellite Communications

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    This study is motivated by the need to give the reader a broad view of the developments, key concepts, and technologies related to information society evolution, with a focus on the wireless communications and geoinformation technologies and their role in the environment. Giving perspective, it aims at assisting people active in the industry, the public sector, and Earth science fields as well, by providing a base for their continued work and thinking

    Data Collection and Capacity Analysis in Large-scale Wireless Sensor Networks

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    In this dissertation, we study data collection and its achievable network capacity in Wireless Sensor Networks (WSNs). Firstly, we investigate the data collection issue in dual-radio multi-channel WSNs under the protocol interference model. We propose a multi-path scheduling algorithm for snapshot data collection, which has a tighter capacity bound than the existing best result, and a novel continuous data collection algorithm with comprehensive capacity analysis. Secondly, considering most existing works for the capacity issue are based on the ideal deterministic network model, we study the data collection problem for practical probabilistic WSNs. We design a cell-based path scheduling algorithm and a zone-based pipeline scheduling algorithm for snapshot and continuous data collection in probabilistic WSNs, respectively. By analysis, we show that the proposed algorithms have competitive capacity performance compared with existing works. Thirdly, most of the existing works studying the data collection capacity issue are for centralized synchronous WSNs. However, wireless networks are more likely to be distributed asynchronous systems. Therefore, we investigate the achievable data collection capacity of realistic distributed asynchronous WSNs and propose a data collection algorithm with fairness consideration. Theoretical analysis of the proposed algorithm shows that its achievable network capacity is order-optimal as centralized and synchronized algorithms do and independent of network size. Finally, for completeness, we study the data aggregation issue for realistic probabilistic WSNs. We propose order-optimal scheduling algorithms for snapshot and continuous data aggregation under the physical interference model

    Resource Allocation and Positioning of Power-Autonomous Portable Access Points

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    Magneto-inductive wireless underground sensor networks: novel longevity model, communication concepts and workarounds to key theoretical issues using analogical thinking

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    This research has attempted to devise novel workarounds to key theoretical issues in magneto-inductive wireless underground sensor networks (WUSNs), founded on analogical thinking (Gassmann & Zeschky 2008). The problem statement for this research can be summarized as follows. There has been a substantial output of research publications in the past 5 years, devoted to theoretically analysing and resolving the issues pertaining to deployment of MI based WUSNs. However, no alternate solution approaches to such theoretical analyses have been considered. The goal of this research was to explore such alternate solution approaches. This research has used the principle of analogical thinking in devising such alternate solution approaches. This research has made several key contributions to the existing body of work. First, this research is the first of its kind to demonstrate by means of review of state-of-the-art research on MI based WUSNs, the largely theoretical genus of the research to the exclusion of alternate solution approaches to circumvent key theoretical issues. Second, this research is the first of its kind to introduce the notion of analogical thinking as a solution approach in finding viable workarounds to theoretical impediments in MI based WUSNs, and validate such solution approach by means of simulations. Third, this research is the first of its kind to explore novel communication concepts in the realm of MI based WUSNs, based on analogical thinking. Fourth, this research is the first of its kind to explore a novel longevity model in the realm of MI based WUSNs, based on analogical thinking. Fifth, this research is also the first to extend the notion of analogical thinking to futuristic directions in MI based WUSNs research, by means of providing possible indicators drawn from various other areas of contemporary research. In essence, the author believes that the findings of this research mark a paradigm shift in the research on MI based WUSNs

    Machine Learning and Signal Processing Design for Edge Acoustic Applications

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    Machine Learning and Signal Processing Design for Edge Acoustic Applications

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    Exploiting and optimizing mobility in wireless sensor networks

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    Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2016.Nos últimos anos, as chamadas Redes de Sensores Sem Fio (RSSF) tem sido usadas numa grande variedade de aplicações, tais como monitoramento (p.ex. poluição do ar e água, vulcões, estruturas, sinais vitais), detecção de eventos (p.ex. vigilância, incêndios, inundações, terremotos), e monitoramento de alvos (p.ex. segurança, animais silvestres, etc). RSSF são constituídas tipicamente por dezenas, as vez centenas de pequenos dispositivos alimentados por baterias, capazes de realizar medições e de transmitir tais dados para uma estação base através de um canal sem fio. Uma das formas mais promissoras para melhorar o desempenho das RSSF em termos de conectividade, tempo de vida da rede, e latência na transmissão dos dados é através de técnicas que exploram a mobilidade em um ou mais componentes da rede. A mobilidade na RSSF pode ser tanto controlável como aleatória, sendo que em ambos os casos os protocolos devem ser devidamente ajustados para responder adequadamente aos cenários em questão. No caso de mobilidade aleatória, os nodos sensores podem ser capazes de aprender os padrões de mobilidade dos nodos para poderem otimizar a operação da rede. Por outro lado, sendo os padrões de mobilidade conhecidos, é possível fazer escolhas para melhor sintonizar o desempenho da rede de acordo com os critérios estabelecidos pelo projetista. A presente tese de doutorado procura explorar as vantagens associadas com o uso de mobilidade controlada em RSSF. É possível definir mobilidade controlada como sendo a capacidade de se alterar propositalmente o posicionamento de determinados nodos da RSSF. Com isso se torna possível explorar, controlar, ou mesmo otimizar a trajetória e a velocidade dos nodos móveis da RSSF a fim de maximizar o desempenho da rede como um todo. Definitivamente, o uso de nodos que permitam o ajuste de trajetória e velocidade oferece um alto grau de flexibilidade para se explorar aspectos de mobilidade e projetar protocolos de coleta de dados otimizados. Ao se utilizar mobilidade controlada, algumas das operações realizadas pela RSSF podem ser significativamente melhoradas, de modo a tornar possível ajustar o padrão de desempenho da rede de acordo com os níveis desejados. Por exemplo, o processo de descoberta de nodos pode ser melhorado e mesmo simplificado com o controle dos nodos móveis, de modo que ele possa se aproximar dos nodos estáticos em instantes pré-determinados. Da mesma forma, o processo de coleta de dados pode ser otimizado se os nodos móveis se moverem mais rapidamente nos locais onde eles precisam coletar menos dados. Entretanto, diversos desafios aparecem neste tipo de contexto. Por exemplo, como se deve escalonar a chegada do(s) nodo(s) móvel(is) e como se deve controlar e otimizar a movimentação em termos de velocidade sem afetar a qualidade de serviço. Nesse contexto, o segundo capítulo da teseapresenta um esquema de estimação de localização de nodos estáticos espalhados ao longo de uma área predeterminada, utilizando-se para tanto de um nodo móvel com mobilidade controlada. Tal informação de posicionamento é muito importante para a organização de uma RSSF. Com isso é possível definir a sua cobertura, os protocolos de roteamento, a forma de coleta de dados e também auxiliar em aplicações de rastreamento e detecção de eventos. O esquema proposto consiste de uma técnica de localização para estimar a posição dos nodos sensor de forma eficiente, usando apenas um nodo móvel e técnicas geométricas simples. O esquema não requer hardware adicional ou mesmo comunicação entre nodos sensores, evitando assim maiores gastos de baterias. A estimativa de posição obtida é precisa e capaz de tolerar um certo grau de obstáculos. Os resultados obtidos ao longo da tese demostram que a precisão de localização pode ser bem ajustada selecionando corretamente a velocidade, o intervalo de transmissão de beacons e o padrão de varredura da área de interesse pelo nodo móvel.Já o terceiro capítulo apresentada uma técnica de otimização para fins de controle da mobilidade do nodo coletor de dados (MDC). Com isso torna-se possível desenvolver um esquema inteligente de coleta de dados na RSSF. Em primeiro lugar, são destacados os fatores que afetam o processo de coleta de dados usando um MDC. Em seguida é apresentado um algoritmo adaptativo que permite ajustar os parâmetros de controlenecessários para modificar os parâmetros de movimentação do MDC. Estes parâmetros permitem que a velocidade do MDC seja ajustada em tempo de execução para otimizaro processo de coleta de dados. Com isso o MDC pode se adaptar às diferentes taxas de coletas de dados impostas por um conjunto de nodos heterogêneos. O esquema proposto apresenta vantagens significativas para RSSF de grande escala e também heterogêneas (onde os sensores possuem taxas de amostragem variáveis). Os resultados obtidos mostram um aumento significativo na taxa de coleta de dados e a redução no tempo total de deslocamento e no número de voltas que o MDC gasta para coletar os dados dos sensores.Por fim, o capítulo 4 propõe um mecanismo de controle de acesso (MAC) adaptado ao cenário de mobilidade, que se ajusta automaticamente de acordo com o padrão de mobilidade do MDC. O mesmo foca umaredução no consumo de energia e na melhoria da coleta de dados, suportando mobilidade e evitando colisões de mensagens. Este protocolo destina-se a aplicações de coleta de dados nas quais os nós sensores têm de reportar periodicamente a um nó receptor ou estação base. O conceito básico é baseado em acesso múltiplo de divisão de tempo, onde a duração do padrão de sono-vigília é definida de acordo com o padrão de mobilidade do MDC. O esquema proposto é capaz de atender tanto mobilidade aleatória quanto controlada por parte do MDC, desde que as RSSF sejam organizadas em cluster. Uma análise de simulação detalhada é realizada para avaliar seu desempenho em cenários mais gerais e sob diferentes condições operacionais. Os resultados obtidos mostram que o nosso esquema proposto supera amplamente oprotocolo 802.15.4 com sinais (beacons) em termos de eficiência energética, tempo de deslocamento do MDC e taxas de coleta de dados.Abstract : One of the promising techniques for improving the performance of a wireless sensor network (WSN), in terms of connectivity, network lifetime, and data latency, is to introduce and exploit mobility in some of the network components. Mobility in WSN can be either uncontrollable or controllable and needs to be optimized in both cases. In the case of uncontrolled mobility, sensor nodes can learn the mobility patterns of mobile nodes to improve network performance. On the other hand, if the mobility is controllable in terms of trajectory and speed, it can be best tuned to enhance the performance of the network to the desired level. This thesis considers the problem of exploiting and optimizing mobility in wireless sensor networks in order to increase the performance and efficiency of the network.First, a location estimation scheme is discussed for static nodes within a given sensor area using a controlled mobile node. Position information of static nodes is very important in WSN. It helps in effective coverage, routing, data collection, target tracking, and event detection. The scheme discusses a localization technique for efficient position estimation of the sensor nodes using a mobile node and simple geometric techniques. The scheme does not require extra hardware or data communication and does not make the ordinary sensor nodes to spend energy on any interaction with neighboring nodes. The position estimation is accurate and efficient enough to tolerate obstacles and only requires broadcasting of beacon messages by the mobile node. Obtained simulation results show that the localization accuracy can be well adjusted by properly selecting the speed, beacon interval, and scan pattern of the mobile node.Second, an optimization technique for controlled mobility of a mobile data collector is presented in order to develop a smart data collection scheme in WSN. In this case, first, the factors affecting the data collection process using an MDC is highlighted. Then, an adaptive algorithm and control parameters that the MDC uses for autonomously controlling its motion is presented. These parameters allow the speed of the MDC to be adjusted at run time in order to adaptively improve the data collection process. Built-in intelligence helps our system adapting to the changing requirements of data collection. Our scheme shows significant advantages for sparsely deployed, large scale sensor networks and heterogeneous networks (where sensors have variable sampling rates). The simulation results show a significant increase in data collection rate and reduction in the overall traverse time and number of laps that the MDC spends for data gathering.Finally, a mobility aware adaptive medium access control (MAC) is proposed for WSNs which automatically adjusts according to the mobility pattern of the MDC, focusing on reducing energy consumption and improving data collection, while supporting mobility and collision avoidance. This protocol is targeted to data collection applications (e.g. monitoring and surveillance), in which sensor nodes have to periodically report to a sink node. The core concept is based on adaptive time division multiple access, where the sleep-wake duration is defined according to the MDC mobility pattern. The proposed scheme is described for random, predictable, and controlled arrival of MDC in cluster-based WSNs. A detailed simulation analysis is carried out to evaluate its performance in more general scenarios and under different operating conditions. The obtained results show that our scheme largely outperforms the commonly used 802.15.4 beacon-enabled and other fixed duty-cycling schemes in terms of energy efficiency, MDC traverse time, and data collection rates

    UAVs for Enhanced Communication and Computation

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    Adaptive Precoding and Resource Allocation in Cognitive Radio Networks

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    In this thesis, we develop efficient resource allocation and adaptive precoding schemes for two scenarios: multiuser MIMO-OFDM and multiuser MIMO based CR networks. In the context of the multiuser MIMO-OFDM CR network, we have developed resource allocation and adaptive precoding schemes for both the downlink (DL) and uplink (UL). The proposed schemes are characterized by both computational and spectral efficiencies. The adaptive precoder operates based on generating degrees of freedom (DoF). The resource allocation has been formulated as a sum-rate maximization problem subject to the upper-limit of total power and interference at primary user constraints. The formulated optimization problem is a mixed integer programming having a combinatorial complexity which is hard to solve, and therefore we separated it into a two-phase procedure to elaborate computational efficiency: Adaptive precoding (DoF assignment) and subcarrier mapping. From the implementation perspective, the resource allocation of the DL is central based processing, but the UL is semi-distributed based. The DL and UL problems are sorted out using the Lagrange multiplier theory which is regarded as an efficient alternative methodology compared to the convex optimization theory. The solution is not only characterized by low-complexity, but also by optimality. Numerical simulations illustrate remarkable spectral and SNR gains provided by the proposed schemes.In dieser Dissertation werden effiziente Ressourcenallokation und adaptive Vorkodierungsverfahren für zwei Szenarios entwickelt: Mehrbenutzer-MIMO-OFDM und Mehrbenutzer-MIMO jeweils basierend auf CR-Netzwerken. Im Bereich der Mehrbenutzer-MIMO-OFDM CR-Netzwerke wurden Verfahren zur Ressourcenallokation und zur adaptiven Vorkodierung jeweils für den Downlink (DL) und den Uplink (UL) entwickelt. Die Ressourcenallokation wurde als Optimierungsproblem formuliert, bei dem die Summenrate maximiert wird, wobei die Gesamtsendeleistung und die Interferenz an den Primärnutzern begrenzt ist. Das formulierte Optimierungsproblem ist ein sogenanntes Mixed-Integer-Programm, dessen kombinatorische Komplexität nur extrem aufwendig lösbar ist. Auf Grund dessen wurde es zur Komplexitätsreduktion in zwei Phasen aufgeteilt: Adaptive Vorkodierung (DoF-Zuordnung) und Subkanalzuordnung. Während die Ressourcenallokation für den DL aus Implementierungssicht ein zentralistischer Prozess ist, kann sie für den UL als semiverteilt eingeordnet werden. Die Aufgabe der zentralen Ressourcenallokation wird gelöst, um die zentrale adaptive Vorkodierung und die Subkanalzuordnung für UL und DL zu verwalten. Die Subkanalzuordnung ist für den DL optimal und effizient gelöst, indem das Problem als konvexes Problem modelliert ist. Für den UL wiederum ist das Problem trotz der Konvexität quasi-optimal gelöst, da in der Problemformulierung eine Begrenzung der Ressourcen pro Benutzer existiert
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