753 resultados para Mobile Sensor Networks


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Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores

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Trabajo de final de carrera enfocado a la simulación de una WSN (Wireless Sensors Networks) mediante el programa Contiki 2.7 y el SO Ubuntu. La idea global del proyecto es conseguir simular un entorno con nodos sensores y, a posteriori, comprobar su correcto funcionamiento en motas reales, comprobando los resultados obtenidos en ambos entornos. De esta manera se puede facilitar la puesta en marcha de este tipo de redes inalámbricas en una aplicación real.

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Tämä diplomityö käsittelee kolmannen sukupolven matkaviestinjärjestelmien kuljetuskerroksen mitoitusta. Nykyisten matkapuhelinverkkojen korvaajiksi suunnitellut kolmannen sukupolven matkaviestinjärjestelmät tulevat yhdistämään perinteisen puhelinviestinnän ja uudenlaiset datapalvelut. Uudet verkot tulevat perustumaan pakettivälitteiseen tiedonsiirtoon joka mahdollistaa molempien liikennetyyppien, puheen sekä datan, siirtämisen samassa verkossa. Tämän ratkaisun uskotaan tarjoavan paremmat mahdollisuudet uusien palvelujen luomiseen ja parantavan tiedonsiirtokapasiteettia. Siirtyminen pakettivälitteiseen tiedonsiirtoon aiheuttaa kuitenkin suuria muutoksia verkkoarkkitehtuurissa. Tässä diplomityössä tarkastellaan tulevien runkoverkkojen mitoitukseen liittyviä näkökohtia sekä muodostetaan alustavia kuljetuskerroksen mitoitusohjeita. Diplomityö on tehty osaksi diplomi-insinöörin tutkintoa Lappeenrannan teknillisessä korkeakoulussa. Työ on tehty Nokia Networksin palveluksessa Helsingissä, vuoden 2000 toisella puoliskolla.

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Nowadays, Wireless Sensor Networks (WSN) arealready a very important data source to obtain data about the environment. Thus, they are key to the creation of Cyber-Physical Systems (CPS). Given the popularity of P2P middlewares as ameans to efficiently process information and distribute services, being able to integrate them to WSN¿s is an interesting proposal. JXTA is a widely used P2P middleware that allows peers to easily exchange information, heavily relying on its main architectural highlight, the capability to organize peers with common interests into peer groups. However, right now, approaches to integrate WSNs to a JXTA network seldom take advantage of peer groups. For this reason, in this paper we present jxSensor, an integrationlayer for sensor motes which facilitates the deployment of CPS¿s under this architecture. This integration has been done taking into account JXTA¿s idiosyncrasies and proposing novel ideas,such as the Virtual Peer, a group of sensors that acts as a single entity within the peer group context.

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The aim of this study was to perform an experimental study to evaluate the proper operation distance between the nodes of a wireless sensor network available on the market for different agricultural crops (maize, physic nut, eucalyptus). The experimental data of the network performance offers to farmers and researchers information that might be useful to the sizing and project of the wireless sensor networks in similar situations to those studied. The evaluation showed that the separation of the nodes depends on the type of culture and it is a critical factor to ensure the feasibility of using WSN. In the configuration used, sending packets every 2 seconds, the battery life was about four days. Therefore, the autonomy may be increased with a longer interval of time between sending packets.

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The evolution of wireless sensor network technology has enabled us to develop advanced systems for real time monitoring. In the present scenario wireless sensor networks are increasingly being used for precision agriculture. The advantages of using wireless sensor networks in agriculture are distributed data collection and monitoring, monitor and control of climate, irrigation and nutrient supply. Hence decreasing the cost of production and increasing the efficiency of production. This paper describes the development and deployment of wireless sensor network for crop monitoring in the paddy fields of Kuttanad, a region of Kerala, the southern state of India.

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Distributed systems are one of the most vital components of the economy. The most prominent example is probably the internet, a constituent element of our knowledge society. During the recent years, the number of novel network types has steadily increased. Amongst others, sensor networks, distributed systems composed of tiny computational devices with scarce resources, have emerged. The further development and heterogeneous connection of such systems imposes new requirements on the software development process. Mobile and wireless networks, for instance, have to organize themselves autonomously and must be able to react to changes in the environment and to failing nodes alike. Researching new approaches for the design of distributed algorithms may lead to methods with which these requirements can be met efficiently. In this thesis, one such method is developed, tested, and discussed in respect of its practical utility. Our new design approach for distributed algorithms is based on Genetic Programming, a member of the family of evolutionary algorithms. Evolutionary algorithms are metaheuristic optimization methods which copy principles from natural evolution. They use a population of solution candidates which they try to refine step by step in order to attain optimal values for predefined objective functions. The synthesis of an algorithm with our approach starts with an analysis step in which the wanted global behavior of the distributed system is specified. From this specification, objective functions are derived which steer a Genetic Programming process where the solution candidates are distributed programs. The objective functions rate how close these programs approximate the goal behavior in multiple randomized network simulations. The evolutionary process step by step selects the most promising solution candidates and modifies and combines them with mutation and crossover operators. This way, a description of the global behavior of a distributed system is translated automatically to programs which, if executed locally on the nodes of the system, exhibit this behavior. In our work, we test six different ways for representing distributed programs, comprising adaptations and extensions of well-known Genetic Programming methods (SGP, eSGP, and LGP), one bio-inspired approach (Fraglets), and two new program representations called Rule-based Genetic Programming (RBGP, eRBGP) designed by us. We breed programs in these representations for three well-known example problems in distributed systems: election algorithms, the distributed mutual exclusion at a critical section, and the distributed computation of the greatest common divisor of a set of numbers. Synthesizing distributed programs the evolutionary way does not necessarily lead to the envisaged results. In a detailed analysis, we discuss the problematic features which make this form of Genetic Programming particularly hard. The two Rule-based Genetic Programming approaches have been developed especially in order to mitigate these difficulties. In our experiments, at least one of them (eRBGP) turned out to be a very efficient approach and in most cases, was superior to the other representations.

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This paper addresses the impact of imperfect synchronisation on D-STBC when combined with incremental relay. To suppress such an impact, a novel detection scheme is proposed, which retains the two key features of the STBC principle: simplicity (i.e. linear computational complexity), and optimality (i.e. maximum likelihood). These two features make the new detector very suitable for low power wireless networks (e.g. sensor networks).

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The assessment of routing protocols for mobile wireless networks is a difficult task, because of the networks` dynamic behavior and the absence of benchmarks. However, some of these networks, such as intermittent wireless sensors networks, periodic or cyclic networks, and some delay tolerant networks (DTNs), have more predictable dynamics, as the temporal variations in the network topology can be considered as deterministic, which may make them easier to study. Recently, a graph theoretic model-the evolving graphs-was proposed to help capture the dynamic behavior of such networks, in view of the construction of least cost routing and other algorithms. The algorithms and insights obtained through this model are theoretically very efficient and intriguing. However, there is no study about the use of such theoretical results into practical situations. Therefore, the objective of our work is to analyze the applicability of the evolving graph theory in the construction of efficient routing protocols in realistic scenarios. In this paper, we use the NS2 network simulator to first implement an evolving graph based routing protocol, and then to use it as a benchmark when comparing the four major ad hoc routing protocols (AODV, DSR, OLSR and DSDV). Interestingly, our experiments show that evolving graphs have the potential to be an effective and powerful tool in the development and analysis of algorithms for dynamic networks, with predictable dynamics at least. In order to make this model widely applicable, however, some practical issues still have to be addressed and incorporated into the model, like adaptive algorithms. We also discuss such issues in this paper, as a result of our experience.

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In the last decade mobile wireless communications have witnessed an explosive growth in the user’s penetration rate and their widespread deployment around the globe. It is expected that this tendency will continue to increase with the convergence of fixed Internet wired networks with mobile ones and with the evolution to the full IP architecture paradigm. Therefore mobile wireless communications will be of paramount importance on the development of the information society of the near future. In particular a research topic of particular relevance in telecommunications nowadays is related to the design and implementation of mobile communication systems of 4th generation. 4G networks will be characterized by the support of multiple radio access technologies in a core network fully compliant with the Internet Protocol (all IP paradigm). Such networks will sustain the stringent quality of service (QoS) requirements and the expected high data rates from the type of multimedia applications to be available in the near future. The approach followed in the design and implementation of the mobile wireless networks of current generation (2G and 3G) has been the stratification of the architecture into a communication protocol model composed by a set of layers, in which each one encompasses some set of functionalities. In such protocol layered model, communications is only allowed between adjacent layers and through specific interface service points. This modular concept eases the implementation of new functionalities as the behaviour of each layer in the protocol stack is not affected by the others. However, the fact that lower layers in the protocol stack model do not utilize information available from upper layers, and vice versa, downgrades the performance achieved. This is particularly relevant if multiple antenna systems, in a MIMO (Multiple Input Multiple Output) configuration, are implemented. MIMO schemes introduce another degree of freedom for radio resource allocation: the space domain. Contrary to the time and frequency domains, radio resources mapped into the spatial domain cannot be assumed as completely orthogonal, due to the amount of interference resulting from users transmitting in the same frequency sub-channel and/or time slots but in different spatial beams. Therefore, the availability of information regarding the state of radio resources, from lower to upper layers, is of fundamental importance in the prosecution of the levels of QoS expected from those multimedia applications. In order to match applications requirements and the constraints of the mobile radio channel, in the last few years researches have proposed a new paradigm for the layered architecture for communications: the cross-layer design framework. In a general way, the cross-layer design paradigm refers to a protocol design in which the dependence between protocol layers is actively exploited, by breaking out the stringent rules which restrict the communication only between adjacent layers in the original reference model, and allowing direct interaction among different layers of the stack. An efficient management of the set of available radio resources demand for the implementation of efficient and low complexity packet schedulers which prioritize user’s transmissions according to inputs provided from lower as well as upper layers in the protocol stack, fully compliant with the cross-layer design paradigm. Specifically, efficiently designed packet schedulers for 4G networks should result in the maximization of the capacity available, through the consideration of the limitations imposed by the mobile radio channel and comply with the set of QoS requirements from the application layer. IEEE 802.16e standard, also named as Mobile WiMAX, seems to comply with the specifications of 4G mobile networks. The scalable architecture, low cost implementation and high data throughput, enable efficient data multiplexing and low data latency, which are attributes essential to enable broadband data services. Also, the connection oriented approach of Its medium access layer is fully compliant with the quality of service demands from such applications. Therefore, Mobile WiMAX seems to be a promising 4G mobile wireless networks candidate. In this thesis it is proposed the investigation, design and implementation of packet scheduling algorithms for the efficient management of the set of available radio resources, in time, frequency and spatial domains of the Mobile WiMAX networks. The proposed algorithms combine input metrics from physical layer and QoS requirements from upper layers, according to the crosslayer design paradigm. Proposed schedulers are evaluated by means of system level simulations, conducted in a system level simulation platform implementing the physical and medium access control layers of the IEEE802.16e standard.

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The use of sensorless technologies is an increasing tendency on industrial drivers for electrical machines. The estimation of electrical and mechanical parameters involved with the electrical machine control is used very frequently in order to avoid measurement of all variables related to this process. The cost reduction may also be considered in industrial drivers, besides the increasing robustness of the system, as an advantage of the use of sensorless technologies. This work proposes the use of a recurrent artificial neural network to estimate the speed of induction motor for sensorless control schemes using one single current sensor. Simulation and experimental results are presented to validate the proposed approach. ©2008 IEEE.

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Esta dissertação tem como objetivo principal propor um nodo (ou nó) sensor sem fio para ser utilizado em redes de sensores sem fio, em sistemas de aquisição de dados de extensômetros. O sistema de aquisição para os extensômetros é baseado na ponte de Wheatstone e de modo a permitir várias configurações de extensômetros. O processamento e a comunicação sem fio é realizada pelo ATmega128RFA1, composto por um microcontrolador e um transceiver Rádio-Frequência com o padrão Zigbee. O nodo foi projetado para garantir confiabilidade na aquisição de dados e ser totalmente controlado remotamente. Entre os parâmetros controláveis estão: o ganho do sinal e a taxa de amostragem. Além disso, o nodo possui recursos para efetuar o equilíbrio da ponte de Wheatstone automaticamente. A escolha de seus componentes, baseou-se em critérios relacionados ao consumo de energia do mesmo e ao custo. Foi concebida uma placa de circuito impresso (PCI) para o nodo, e sobre ela foram realizadas estimativas sobre o consumo de energia e valor agregado do protótipo, com o objetivo de analisar a sua viabilidade. Além do projeto do nodo sensor, o trabalho apresenta a proposta de integração do mesmo em uma rede de sensores sem fio (RSSF), incluindo a sugestão do hardware complementar e desenvolvimentos dos softwares. Para os testes do nodo sensor, foi construido experimentalmente um transdutor de força.

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Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques.

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The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.

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Wireless sensor networks can transform our buildings in smart environments, improving comfort, energy efficiency and safety. Today however, wireless sensor networks are not considered reliable enough for being deployed on large scale. In this thesis, we study the main failure causes for wireless sensor networks, the existing solutions to improve reliability and investigate the possibility to implement self-diagnosis through power consumption measurements on the sensor nodes. Especially, we focus our interest on faults that generate in-range errors: those are wrong readings but belong to the range of the sensor and can therefore be missed by external observers. Using a wireless sensor network deployed in the R\&D building of NXP at the High Tech Campus of Eindhoven, we performed a power consumption characterization of the Wireless Autonomous Sensor (WAS), and studied through some experiments the effect that faults have in the power consumption of the sensor.