Dissertations / Theses on the topic 'Distributed sensors networks'
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Mehrotra, Shashank. "Distributed Algorithms for Tasking Large Sensor Networks." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/33975.
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Recent advances in wireless communications along with developments in low-power circuit design and micro-electro mechanical systems (MEMS) have heralded the advent of compact and inexpensive wireless micro-sensor devices. A large network of such sensor nodes capable of communicating with each other provides significant new capabilities for automatically collecting and analyzing data from physical environments.
A notable feature of these networks is that more nodes than are strictly necessary may be deployed to cover a given region. This permits the system to provide reliable information, tolerate many types of faults, and prolong the effective service time. Like most wireless systems, achieving low power consumption is a key consideration in the design of these networks. This thesis presents algorithms for managing power at the distributed system level, rather than just at the individual node level. These distributed algorithms allocate work based on user requests to the individual sensor nodes that comprise the network. The primary goal of the algorithms is to provide a robust and scalable approach for tasking nodes that prolongs the effective life of the network.
Theoretical analysis and simulation results are presented to characterize the behavior of these algorithms. Results obtained from simulation experiments indicate that the algorithms can achieve a significant increase in the life of the network. In some cases this may be by an order of magnitude. The algorithms are also shown to ensure a good quality of sensor coverage while improving the network life. Finally, they are shown to be robust to faults and scale to large numbers of nodes.Master of Science
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Wang, Yu. "A Low-Complexity Distributed Architecture for Wireless Sensors Networks." Thesis, University of Essex, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.504839.
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Feitosa, Allan Eduardo. "Classification techniques for adaptive distributed networks and aeronautical structures." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/3/3142/tde-05022019-104746/.
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This master thesis is the result of a collaborative work between EMBRAER and the Escola Politécnica da USP for the study of structural health monitoring (SHM) techniques using sensors applied to aircraft structures. The goal was to develop classification techniques to discriminate between different events arising in the aircraft structure during tests; in the short term, improving the current SHM system used by EMBRAER, based on acoustic emission and, in the long term, fostering the development of a fully distributed system. As a result of studying classification methods for immediate use, we developed two techniques: the Spectral Similarity and a Support Vector Machines (SVM) classifier. Both are unsupervised solutions, due to the unlabeled nature of the data provided. The two solutions were delivered as a final product to EMBRAER for prompt use in the existing SHM system. By studying distributed solutions for future implementations, we developed a detection algorithm based on adaptive techniques. The main result was a special initialization for a maximum likelihood (ML) detector that yields an exponential decay rate in the error probability to a nonzero steady state, using adaptive diffusion estimation in a distributed sensor network. The nodes that compose the network must decide, locally, between two concurrent hypotheses concerning the environment state where they are inserted, using local measurements and shared estimates coming from their neighbors. The exponential performance does not depend on the adaptation step size value, provided it is sufficiently small. The results concerning this distributed detector were published in the journal IEEE Signal Processing Letters.Esta dissertação de mestrado é o resultado de um trabalho colaborativo entre a EMBRAER e a Escola Politécnica da USP no estudo de técnicas de monitoramento do estado de saúde de estruturas (Structural Health Monitoring - SHM) utilizando sensores em estruturas aeronáuticas. O objetivo foi desenvolver técnicas de classificação para discriminar entre diferentes eventos que surgem em estruturas aeronáuticas durante testes; para o curto prazo, aperfeiçoando o atual sistema de SHM utilizado pela EMBRAER, baseado em emissão acústica e, no longo prazo, fomentando o desenvolvimento de um sistema completamente distribuído. Como resultado do estudo de métodos de classificação para uso imediato, desenvolvemos duas técnicas: a Similaridade Espectral e um classificador que utiliza Support Vector Machines (SMV). Ambas as técnicas são soluções não-supervisionadas, devido a natureza não rotulada dos dados fornecidos. As duas soluções foram entregues como um produto final para a EMBRAER para pronta utilização em seu atual sistema de SHM. Ao estudar soluções completamente distribuídas para futuras implementações, desenvolvemos um algoritmo de detecção baseado em técnicas adaptativas. O principal resultado foi uma inicialização especial para um detector de máxima verossimilhança (maximum likelihood - ML) que possui uma taxa de decaimento exponencial na probabilidade de erro até um valor não nulo em regime estacionário, utilizando estimação adaptativa em uma rede distribuída. Os nós que compõem a rede devem decidir, localmente, entre duas hipóteses concorrentes com relação ao estado do ambiente onde eles estão inseridos, utilizando medidas locais e estimativas compartilhadas vindas de nós vizinhos. O desempenho exponencial não depende do valor do passo de adaptação, se este for suficientemente pequeno. Os resultas referentes a este detector distribuído foram publicados na revista internacional IEEE Signal Processing Letters.
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Chatterjea, Supriyo. "Distributed and self-organizing data management strategies for wireless sensors networks a cross-layered approach /." Enschede : University of Twente [Host], 2008. http://doc.utwente.nl/59799.
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Karaaslan, Ibrahim. "Anti-sensor Network: Distortion-based Distributed Attack In Wireless Sensor Networks." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/3/12609276/index.pdf.
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In this thesis, a novel anti-sensor network paradigm is introduced against wireless sensor networks (WSN). Anti-sensor network (ASN) aims to destroy application reliability by adaptively and anonymously introducing adequate level of artificial distortion into the communication of the event features transported from the sensor nodes (SN) to the sink. ASN is composed of anti-sensor nodes (aSN) randomly distributed
over the sensor network field. aSNs pretend to be SNs tomaintain anonymity and so improve resiliency against attack detection and prevention mechanisms. Performance
evaluations via mathematical analysis and simulation experiments show that ASN can effectively reduce the application reliability of WSN.
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Murukesvan, Abhinash. "Distributed Overlays in Wireless Sensor Networks." Thesis, KTH, Kommunikationssystem, CoS, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-92202.
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This thesis investigates two architectures and compares their suitability for selective application and user differentiation in sensor networks. A hierarchical architecture consisting of more capable cluster heads surrounded by weaker nodes is compared to a flat architecture of equally powerful nodes. In both architectures there exists a logical overlay network that connects the nodes, depending on the application and user. Furthermore, a broadcast encryption scheme is proposed to aid in distributing keys to nodes for secure communication and to maintain these restricted groups.applikation och användar differentiering i trådlösa sensor nätverk. En hierarkisk arkitekturbestående av kraftfullare sensor noder omgiven av mindre kraftfulla sensor noder jämförsmed en platt arkitektur bestående av lika kraftfulla sensor noder. I båda arkitekturer existerarett logiskt lager ovanpå stacken som kopplar noder beroende på applikation och användare,helt oberoende av geografisk placering. Utöver det, bör en nyckel management schema användas till att distribuera nycklar tillnoderna för säker kommunikation och att bibehålla dessa slutna grupper.
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Lin, Erwei Kam Moshe. "Detection in distributed sensor networks /." Philadelphia, Pa. : Drexel University, 2005. http://hdl.handle.net/1860/1303.
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Gao, Huaien. "Distributed learning in sensor networks." Diss., lmu, 2009. http://nbn-resolving.de/urn:nbn:de:bvb:19-96120.
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MORBEE, MARLEEN. "Optimized information processing in resource-constrained vision systems. From low-complexity coding to smart sensor networks." Doctoral thesis, Universitat Politècnica de València, 2011. http://hdl.handle.net/10251/12126.
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Vision systems have become ubiquitous. They are used for traffic monitoring, elderly care, video conferencing, virtual reality, surveillance, smart rooms, home automation, sport games analysis, industrial safety, medical care etc. In most vision systems, the data coming from the visual sensor(s) is processed before transmission in order to save communication bandwidth or achieve higher frame rates. The type of data processing needs to be chosen carefully depending on the targeted application, and taking into account the available memory, computational power, energy resources and bandwidth constraints.
In this dissertation, we investigate how a vision system should be built under practical constraints. First, this system should be intelligent, such that the right data is extracted from the video source. Second, when processing video data this intelligent vision system should know its own practical limitations, and should try to achieve the best possible output result that lies within its capabilities. We study and improve a wide range of vision systems for a variety of applications, which go together with different types of constraints.
First, we present a modulo-PCM-based coding algorithm for applications that demand very low complexity coding and need to preserve some of the advantageous properties of PCM coding (direct processing, random access, rate scalability). Our modulo-PCM coding scheme combines three well-known, simple, source coding strategies: PCM, binning, and interpolative coding. The encoder first analyzes the signal statistics in a very simple way. Then, based on these signal statistics, the encoder simply discards a number of bits of each image sample. The modulo-PCM decoder recovers the removed bits of each sample by using its received bits and side information which is generated by interpolating previous decoded signals. Our algorithm is especially appropriate for image coding.Morbee, M. (2011). Optimized information processing in resource-constrained vision systems. From low-complexity coding to smart sensor networks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/12126
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Boschian, Valentina. "Models and Methods for Multi-Actor Systems." Doctoral thesis, Università degli studi di Trieste, 2012. http://hdl.handle.net/10077/7431.
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2010/2011The study of the models and methods to apply to multi-actor systems is a widely discussed research topic in the related scientific literature. The multi-actor systems are defined as systems that are characterized by the presence of several autonomous elements, of different decision makers and of complex rules that allow the communication, the coordination and the connection of the components of such systems. Commonly, the study of Multi-Actor System, MAS, recalls the well-known issues concerning the multi-agent systems. The research topic related to the multi-agent system firstly started to appear in scientific literature in 1980s, mainly in relation to the computer science and artificial intelligence. In this dissertation, in particular, the study of the multi-agent systems, and specifically of the multi-actor systems, is taken into account merely in relation to the distinctive features of complexity that characterize such systems and not to the issues concerning the agent-oriented software engineering. Therefore, the research results presented in this thesis are focused on the development and on the realization of innovative models and methodologies to face the management and the decision making mechanisms applied to complex multi-actor systems. This dissertation especially focuses on two different examples of multi-actor systems in two very diverse perspectives. The former deals with the research problem related to intermodal transportation networks, while the latter with the so called consensus problem in distributed networks of agents. Concerning the research problem related to the intermodal logistic systems, the research activity addresses the management of their more and more increasing complexity by the applications of the modern Information and Communication Technologies (ICT) tools that are key solutions to achieve the efficiency and to enhance logistics competitiveness. The related scientific literature still seems lacking in addressing with adequate attention the impact of these new techniques on the management of these complex systems and, moreover, there is an apparent lack of a systematic and general methodology to describe in detail the multiplicity of elements that can influence the dynamics and the corresponding information and decision making structure of intermodal transportation systems. The innovative results presented in this dissertation are focused on the development of an Integrated System, IS, devoted to manage intermodal transportation networks at the tactical as well as operational decision level to be used by decision makers both in off-line planning and real time management. To specify the Integrated System, a reference model is developed relying on a top-down metamodeling procedure. These innovative research results are a contribution to bridge the gap and to propose not only a systematic modeling approach devoted to describe a generic multi-actor logistic system, but also a management technique based on a closed loop strategy. The second example of application is focused on a topic that is widely discussed in scientific literature related to the study of the multi-actor collective behaviors in a distributed network. The interaction protocols that allow the agents to reach the convergence to a common value is called consensus or agreement problem. This research problem is particularly studied in the context of cooperative control of multi-agent systems because the agents are autonomous, independent and have to interact in a distributed network. The presented research results address the investigation of new and fast alignment protocols that enhance the performances of the standard iteration protocols for particular topologies of digraphs on the basis of a triangular splitting of the standard iteration matrix. The examined examples, the models and the methodologies applied to analyze them, are very different in the two cases and this testifies the large extent of research problems related to the multi-actor systems.
L’analisi di modelli e metodi da sviluppare e da applicare nel contesto dei sistemi multi-attoriali costituisce un tema molto variegato e discusso nella letteratura scientifica internazionale. I sistemi multi-attoriali sono sistemi che si contraddistinguono per la presenza di molti elementi autonomi diversi tra loro, di molteplici decisori e di complesse regole che determinano la comunicazione, il coordinamento e la connessione all'interno di tali sistemi. Frequentemente, facendo riferimento a sistemi multi-attoriali, Multi-Actor Systems, si richiama il tema molto attuale dei sistemi multi agente, Multi-Agent Systems. Diffusisi a partire dal 1980, i sistemi multi agente sono spesso studiati in relazione alle metodologie di sviluppo dell'ingegneria del software. Nel presente lavoro di tesi, il tema dei sistemi multi-agente, ed in particolare di quelli multi-attoriali, non viene analizzato in questo contesto, ma in relazione alle tecniche decisionali da adottare per gestire sistemi caratterizzati da un alto livello di complessità. In tale ambito, i risultati presentati all'interno di questa dissertazione sono focalizzati sullo sviluppo e sulla realizzazione di nuovi metodi e di nuove metodologie, in grado di affrontare la gestione della complessità dei sistemi multi-attoriali. Vengono in particolare esaminate due diverse problematiche, in due contesti completamente diversi e con tecniche differenti, a testimoniare le vaste applicazioni che riguardano i sistemi multi-attoriali. I problemi analizzati sono incentrati, in primo luogo, su un'applicazione inerente la gestione di sistemi logistici intermodali ed, in secondo luogo, sullo studio delle regole o protocolli di interazione in una rete distribuita di agenti autonomi. Per quanto riguarda l'aspetto legato ai sistemi intermodali di trasporto, un tema molto discusso nella letteratura scientifica recente, l'analisi si focalizza sulla gestione della loro sempre crescente complessità, tramite l'utilizzo di sistemi dell'Information and Communication Technology, ICT. Questi strumenti richiedono metodi e modelli che sono innovativi rispetto a quanto è presente nella letteratura scientifica, all'interno della quale è stata riscontrata la mancanza di un approccio sistematico e sufficientemente ad alto livello per la realizzazione di una metodologia in grado di descrivere allo stesso tempo sia la molteplicità di elementi che influenzano le dinamiche e le informazioni, sia le strutture decisionali dei sistemi intermodali. L'innovazione dei risultati presentati in questa tesi si focalizza proprio sull'esigenza di proporre un sistema integrato, Integrated System (IS), basato su un metamodello delle reti intermodali di trasporto, che fornisca un valido supporto ai decisori sia a livello tattico che operativo. Il secondo aspetto affrontato in questa tesi riguarda un altro argomento di largo ed attuale interesse nella letteratura scientifica, che viene comunemente chiamato problema del consenso. Questo problema affronta lo studio di come diversi agenti autonomi collocati su una rete distribuita siano in grado di comunicare e di accordarsi su un valore comune, senza la presenza di un decisore centrale. A questo scopo ci sono degli algoritmi che specificano le regole o protocolli di interazione tra i diversi agenti. In tale contesto, i risultati proposti si focalizzano su alcune problematiche rappresentate dal protocollo classico del consenso e soprattutto sulla sua scarsa efficienza in particolari conformazioni delle reti di agenti. Il lavoro di tesi propone, quindi, un approccio di suddivisione, splitting, della matrice standard di iterazione, di tipo triangolare, che presenta notevoli vantaggi in termini di performance rispetto all'algoritmo classico. Lo studio di problemi multi-attoriali, pertanto, richiede lo sviluppo di innovative metodologie decisionali e di nuovi metodi di gestione delle comunicazioni, per rispondere al livello sempre crescente di complessità, offrendo in questo modo alcuni spunti molto interessanti per la ricerca.
XXIV Ciclo
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Oreshkin, Boris. "Distributed information fusion in sensor networks." Thesis, McGill University, 2010. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=86916.
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This thesis addresses the problem of design and analysis of distributed in-network signal processing algorithms for effcient aggregation and fusion of information in wireless sensor networks. The distributed in-network signal processing algorithms alleviate a number of drawbacks of the centralized fusion approach. The single point of failure, complex routing protocols, uneven power consumption in sensor nodes, ineffcient wireless channel utilization, and poor scalability are among these drawbacks. These drawbacks of the centralized approach lead to reduced network lifetime, poor robustness to node failures, and reduced network capacity. The distributed algorithms alleviate these issues by using simple pairwise message exchange protocols and localized in-network processing. However, for such algorithms accuracy losses and/or time required to complete a particular fusion task may be significant. The design and analysis of fast and accurate distributed algorithms with guaranteed performance characteristics is thus important. In this thesis two specific problems associated with the analysis and design of such distributed algorithms are addressed.For the distributed average consensus algorithm a memory based acceleration methodology is proposed. The convergence of the proposed methodology is investigated. For the two important settings of this methodology, optimal values of system parameters are determined and improvement with respect to the standard distributed average consensus algorithm is theoretically characterized. The theoretical improvement characterization matches well with the results of numerical experiments revealing significant and well scaling gain. The practical distributed on-line initialization scheme is devised. Numerical experiments reveal the feasibility of the proposed initialization scheme and superior performance of the proposed methodology with respect to several existing acceleration approaches.
For the collaborative signal and information processing methodology a number of theoretical performance guarantees is obtained. The collaborative signal and information processing framework consists in activating only a cluster of wireless sensors to perform target tracking task in the cluster head using particle filter. The optimal cluster is determined at every time instant and cluster head hand-off is performed if necessary. To reduce communication costs only an approximation of the filtering distribution is sent during hand-off resulting in additional approximation errors. The time uniform performance guarantees accounting for the additional errors are obtained in two settings: the subsample approximation and the parametric mixture approximation hand-off.
Cette thèse aborde le problème de la conception et l'analyse d'algorithmes distribuès servant à l'agrégation efficace et la fusion de l'information dans des reséaux capteurs sans fil. Ces algorithmes distribuès servent à addresser un bon nombre d'inconvénients qu'ont les approches de fusion centralisée telles que le point de défaillance unique, les protocoles de routage complexe, la consommation de puissance inégale dans les noeuds de capteurs, l'utilisation inefficace des voies de transmission sans-fil et l'extensibilité limitée. Ces inconvénients de l'approche centralisée ont comme effet de réduire la durée de vie du reséau, la robustesse des noeuds face aux défaillances et la capacité du réseau. Les algorithmes distribuès atténuent ces problèmes en utilisant des simples protocoles de messageries entre les noeuds ainsi que du traitement d'information localisé. Toutefois, pour ces algorithmes, les pertes de précision et/ou de temps nécessaire pour effectuer une tâche peuvent être importantes. C'est pourquoi la conception et l'analyse d'algorithmes distribuès rapide et précis est importante. Dans cette thèse, deux problèmes spécifiques associés à l'analyse et le conception de tels algorithms sont abordés.
En ce qui concerne l'algorithme de consensus sur la moyenne distribuè, une méthode d'accélération fondé sur la mémoire est proposée et sa convergence analysée. Pour les deux paramètres importants de cette méthodologie, les valeurs optimales pour le système sont déterminées et l'amélioration par rapport à l'algorithme de consensus de base est caractérisée de façon théorique. Cette caractérisation correspond aux resultants d'expériences numériques et révèlent des gains importants et extensibles. Le régime distribuè d'initialisation en ligne est conçu. Des expériences numériques révèlevent la faisabilité du régime d'initilisation proposé ainsi qu'un rendement supérieur à plusieurs approches existantes.
Pour la méthodologie de traitement de signaux et d'information collaborative, un certain nombre de garanties théoriques de performance sont obtenues. Ce cadre de travail consiste à activer seulement une grappe de capteurs sans fil pour effectuer les tâches de pistage d'objet au niveau deu chef de groupe en utilisant un filtre particulaire. La grappe optimale est déterminée à chaque intervale de temps et le transfert du titre de chef de groupe est réalisé au besoin. Pour réduire les coûts de communication, seulement une approximation de la distribution du filtre est envoyé pendant le transfert de responsabilités ce qui entraîne des erreurs supplémentaires. Les garanties de performance uniformes dans le temps tenant compte de ces erreurs supplémentaires sont obtenues dans deux contextes.
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Wen, Xiaojun. "Distributed MIMO for wireless sensor networks." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/5749.
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Over the past decade, wireless sensor networks have gained more research attention for their potential applications in healthcare, defense, environmental monitoring, etc. Due to the strict energy limitation in the sensor node, techniques used for energy saving are necessary for this kind of network. MIMO technology is proven to be an effective method of increasing the channel capacity and supporting higher data rate under a fixed power budget and bit-error-rate requirement. So, wireless sensor networks and MIMO technology are combined and investigated in this thesis. The key contributions of this thesis are detailed below. Firstly, the extended total energy consumption equations for different transmission modes in cluster-based wireless sensor networks are derived. The transmitting energy consumption and the circuit energy consumption are taken into account in both intra-cluster and inter-cluster phases respectively. Secondly, a resource allocation framework is proposed for cluster-based cooperative MIMO on consideration of circuit energy. By introducing two adjusting parameters for the transmitting energy and the time slot allocation between intra-cluster and inter-cluster phases, this framework is designed to achieve the maximum data throughput of the whole system whilst maintaining the capacity and outage probability requirement in these two phases respectively. Thirdly, on comparison of various transmission modes in wireless sensor networks, a relatively energy-efficient mode switching framework is proposed for both single-hop and multi-hop transmissions. Based on the destination and the neighboring nodes’ path-loss, the source node can decide which transmission mode, SISO or cooperative MISO, single-hop or multi-hop, should be chosen. Conditions for each mode switching are investigated. The possible existing area of the cooperative nodes and the relaying nodes can be obtained from this framework.
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Ramakrishnan, Naveen. "Distributed Learning Algorithms for Sensor Networks." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1284991632.
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Chan, Chee Wai. "Distributed beamforming in wireless sensor networks." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Dec%5FChan.pdf.
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Thesis (M.S. in Engineering Science (Electrical Engineering))--Naval Postgraduate School, Dec. 2004.Thesis Advisor(s): Murali Tummala, Roberto Cristi. Includes bibliographical references (p. 79-81). Also available online.
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Kulathumani, Vinodkrishnan. "Network Abstractions for Designing Reliable Applications Using Wireless Sensor Networks." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1211560039.
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Li, Junlin. "Distributed estimation in resource-constrained wireless sensor networks." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26633.
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Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009.Committee Chair: Ghassan AlRegib; Committee Member: Elliot Moore; Committee Member: Monson H. Hayes; Committee Member: Paul A. Work; Committee Member: Ying Zhang. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Wälchli, Markus. "Distributed event detection in wireless sensor networks /." [S.l.] : [s.n.], 2009. http://opac.nebis.ch/cgi-bin/showAbstract.pl?sys=000288149.
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Cheung, Victor. "Distributed position estimation for wireless sensor networks /." View abstract or full-text, 2006. http://library.ust.hk/cgi/db/thesis.pl?COMP%202006%20CHEUNG.
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Üstebay, Deniz. "Efficient distributed consensus in wireless sensor networks." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=114428.
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Many applications of wireless sensor networks can be formulated as instances of the distributed average consensus problem. This problem involves reaching a network state where each node has the same value---the average of the initial values. Reaching a consensus can be challenging in practical scenarios where the network topology varies in time due to node mobility or unreliable wireless communication links. Randomized gossip algorithms are attractive methods for such scenarios because they do not require specialized routes; they rely on asynchronous updates between random pairs of nodes. However, the communication overhead of gossip is high on topologies that are generally used for modeling wireless sensor networks. Here we propose novel gossip algorithms that reach the consensus with fewer wireless transmissions compared to randomized gossip.We first propose greedy gossip with eavesdropping. This algorithm takes advantage of the broadcast nature of wireless transmissions such that nodes eavesdrop on the updates in their neighborhood. Consequently, when a node wakes up for gossip update, instead of choosing a neighbor randomly, it chooses the neighbor which has the most different value than its own. We prove that greedy updates in this fashion are guaranteed to converge faster than randomized gossip and the communication savings can be expressed as a function of the maximum number of neighbors in the network.Then we move on to studying the problem of reaching consensus on a high-dimensional vector. Although consensus on the entries of a vector can be achieved by running gossip in parallel for each entry, this can be wasteful when only few entries of the vector are significant. This thesis presents threshold and top-m selective gossip algorithms which aim to reach a consensus only on the significant entries of the consensus vector. Both algorithms focus communication resources at each update on exchanging only the significant entries of the local vectors. We prove that such myopic updates identify the significant entries of the consensus vector successfully. Using these algorithms, we propose novel approaches to decentralized compression and distributed particle filtering in wireless sensor networks. Numerical experiments demonstrate communication savings over existing methods.The methods proposed in this thesis are appropriate alternatives to randomized gossip because they do not require additional information to be transmitted beyond local neighborhoods. Taken together our results indicate that it is possible to decrease the communication overhead of randomized gossip while preserving its attractive properties.De nombreuses applications des réseaux de capteurs sans fil peuvent être formulées comme des cas particuliers du problème de consensus moyenné distribué. Ce problème nécessite d'atteindre un état du réseaux où tous les capteurs ont la même valeur; à savoir la moyenne des valeurs initiales. Arriver à un tel consensus peut représenter un défi dans certains scénarios pratiques si la topologie du réseau change au cours du temps, par exemple à cause de la mobilité des capteurs ou un manque de fiabilité des liens sans fil. Dans ces cas particuliers, les algorithmes de colportage sont des alternatives attrayantes étant donné qu'ils n'ont pas besoin de routes spécifiques: ils dépendent d'échanges asynchrones effectués entre les capteurs. Cependant, la communication supplémentaire ajoutée par le colportage est élevée pour les topologies utilisées pour modeler les réseaux de capteurs sans fil. Nous proposons ici de nouveaux algorithmes de colportage qui arrivent à un consensus en utilisant moins de transmissions sans fil que le colportage aléatoire. Nous proposons tout d'abord un algorithme de colportage avec écoute du voisinage. Cet algorithme profite de la nature des transmissions sans fils pour épier les échanges dans le voisinage. Ainsi, quand un noeud se réveille pour une mise à jour de l'algorithme de colportage, au lieu de choisir un noeud voisin en manière aléatoire, il choisit le voisin qui a la valeur la plus éloignée de la sienne. Nous prouvons que ces mises à jour sont garanties de converger plus rapidement que le colportage aléatoire et que l'économie en terme de communication peut être exprimée en fonction du nombre maximum de voisins dans le réseau. Nous étudions ensuite le problème d'arriver à un consensus sur un vecteur de grande dimension. Le consensus sur les composantes d'un vecteur peut être réalisé avec l'utilisation du colportage en parallèle pour chaque composante. Cependant cette façon peut être peu économique dans le cas où seulement quelques composantes sont significatives. Cette thèse présente deux algorithmes, dénommés colportage sélectif seuil et top-m, qui visent à arriver à un consensus seulement sur les composantes significatives du vecteur considéré. Les deux algorithmes se focalisent sur l'utilisation des ressources de communication à chaque mise à jour en échangant seulement les composantes significatives du vecteur local. Nous prouvons que de telles mises à jour identifient avec succès les composantes significatives du vecteur. Utilisant ces algorithmes, nous proposons de nouvelles méthodes pour la compression décentralisée et les filtres à particules distribués dans les réseaux de capteurs. Nos expériences numériques démontrent que des économies de communication sont réalisées sur les méthodes existantes. Les algorithmes proposés dans cette thèse sont des alternatives appropriées au colporatage aléatoire parce qu'ils n'ont pas besoin de l'information additionnelle qui doit être transmise au-delà du voisinage proche. Pris dans leur ensemble, nos résultats indiquent qu'il est possible de diminuer l'excès de communication du colportage aléatoire tout en gardant ses propriétés bénéfiques.
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Luo, Bin, and 羅斌. "Distributed clock synchronization for wireless sensor networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/198812.
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Clock synchronization for Wireless Sensor Networks (WSNs) has attracted lots of attention due to its importance for operations in WSNs. In traditional centralized clock synchronization algorithms, all the local information should be transmitted to a fusion center for processing, and the results need to be forwarded back to each individual sensor, thus resulting in a heavy burden on communication and computation in the network. In addition, it also lacks of adaptability to link failures and dynamic changes in the network topology, which greatly prevents their use in WSNs. Hence, in this thesis, we focus on developing energy-efficient distributed clock synchronization algorithms for WSNs.
Firstly, global clock synchronization problem is investigated with time-varying clock parameters (skew and offset) owing to imperfect oscillator circuits. A distributed Kalman filter is developed for clock parameters tracking. The proposed algorithm only requires each node to exchange limited information with its direct neighbors, thus is energy efficient, scalable with network size, and is robust against changes in network connectivity. A low-complexity distributed algorithm based on Coordinate-Descent with Bootstrap (CD-BS) is also proposed to provide rapid initialization of the tracking algorithm. Simulation results show that the proposed distributed tracking algorithm achieves the long-term accuracy for the clock parameters close to the Bayesian Cramer-Rao Lower Bound.
Secondly, the problem of global clock synchronization for WSNs in the presence of unknown exponential delays is studied. The joint maximum likelihood estimator of clock offsets, clock skews and fixed delays of the network is first formulated as a global linear programming (LP) problem. Based on the Alternating Direction Method of Multipliers (ADMM), we propose a fully-distributed synchronization algorithm that has low communication overhead and computation cost. Simulation results show that the proposed algorithm achieves better accuracy than consensus algorithm and the distributed least squares algorithm, and can always converge to the centralized optimal solution.
Finally, global clock synchronization for WSNs under the exponentially distributed delays is re-visited with the fast convergence min-sum algorithm. The synchronization problem is cast into an optimization problem represented by factor graph, and a closed-form expression of the messages passed between nodes are derived. Simulation results show that this distributed algorithm can approach the centralized LP solution with faster convergence speed compared to ADMM-based algorithm.published_or_final_version
Electrical and Electronic Engineering
Doctoral
Doctor of Philosophy
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Yang, Shusen. "Distributed optimisation in dynamic wireless sensor networks." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/19676.
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Over the past decade, Wireless Sensor Networks (WSNs) have evolved into a hot interdisciplinary research area. WSNs are generally considered to be statically deployed, but in reality they are dynamic in nature due to a variety of characteristics including fluctuating wireless link quality and clock drift. Furthermore, new WSN topologies and applications have introduced more dynamics, such as time-varying power resources, data traffic patterns, and mobile sensing. These dynamics pose challenges to the theoretical understanding of WSN behaviours and the design of practical algorithms. This thesis investigates distributed network optimisation in three types of dynamic WSNs: WSNs powered by time-varying solar energy, WSNs with fluctuating wireless channel quality, and WSNs with mobile relays and mobile sinks. In distributed optimisation, sensor nodes communicate with each other to collaboratively solve the overall network optimisation problem. Realistic models are established for these dynamic WSNs, and efficient distributed algorithms are developed to optimise network performance, including power management, duty cycling, wireless link scheduling, data routing and forwarding, sensing rate control, and network resource allocation and pricing. Considering the limited capacity of typical sensor nodes, this thesis also aims to understand and balance the tradeoff between system performance and complexity, bridging the gap between optimisation theory and practical algorithm design in dynamic WSNs. The proposed algorithms are shown to outperform state-of-the-art schemes through theoretical analysis, simulations, and real testbed experiments. The work presented in this thesis should be of interest to researchers in the areas of general embedded networked systems and wireless networks. It should also prove useful in emerging research areas including the Internet of Things (IoTs), Cyber-Physical Systems (CPS), and Information and Communications Technology (ICT) for smart sustainable cites.
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De, Jager Dirk. "Enabling technologies for distributed body sensor networks." Thesis, University of Southampton, 2012. https://eprints.soton.ac.uk/340622/.
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Low Power Wireless Sensor Networks, Preventative Healthcare and Pervasive Systems are set to provide long-term continuous monitoring, diagnosis and care for patients in the next few years. Distributed forms of these networks are investigated from a holistic point of view. Individual components of these systems including: sensors, software and hardware implementations are investigated and analysed. Novel sensors are developed for low power capturing of Body Sensor Network (BSN) information to enable long term use. Software frameworks are designed to enable these technologies to run on low power nodes as well as enabling them to perform evaluation of their data before transmission into the network. An architecture is designed to enable task distribution to intensive processing from low power nodes. Two forms of distributed BSNs are also developed: a horizontal network and a vertical network. It is shown that using these two types of networks enables information and task distribution allowing low power sensing nodes to evaluate information before transmission. These systems have the opportunity to revolutionalise expensive acute episodic care systems of today, but are not currently being implemented or investigated to the extent that they could. The technological barriers to entry are addressed in this thesis with the investigation and evaluation of distributed body sensor networks. It is shown that horizontal networks can distribute information eficiently, while vertical networks can distribute processing eficiently.
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Jabeen, Farhana. "Distributed spatial analysis in wireless sensor networks." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/distributed-spatial-analysis-in-wireless-sensor-networks(f8a1f71a-81b0-4dc7-b520-b90a2393a61e).html.
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Wireless sensor networks (WSNs) allow us to instrument the physical world in novel ways, providing detailed insight that has not been possible hitherto. Since WSNs provide an interface to the physical world, each sensor node has a location in physical space, thereby enabling us to associate spatial properties with data. Since WSNs can perform periodic sensing tasks, we can also associate temporal markers with data. In the environmental sciences, in particular, WSNs are on the way to becoming an important tool for the modelling of spatially and temporally extended physical phenomena. However, support for high-level and expressive spatial-analytic tasks that can be executed inside WSNs is still incipient. By spatial analysis we mean the ability to explore relationships between spatially-referenced entities (e.g., a vineyard, or a weather front) and to derive representations grounded on such relationships (e.g., the geometrical extent of that part of a vineyard that is covered by mist as the intersection of the geometries that characterize the vineyard and the weather front, respectively). The motivation for this endeavour stems primarily from applications where important decisions hinge on the detection of an event of interest (e.g., the presence, and spatio-temporal progression, of mist over a cultivated field may trigger a particular action) that can be characterized by an event-defining predicate (e.g., humidity greater than 98 and temperature less than 10). At present, in-network spatial analysis in WSN is not catered for by a comprehensive, expressive, well-founded framework. While there has been work on WSN event boundary detection and, in particular, on detecting topological change of WSN-represented spatial entities, this work has tended to be comparatively narrow in scope and aims. The contributions made in this research are constrained to WSNs where every node is tethered to one location in physical space. The research contributions reported here include (a) the definition of a framework for representing geometries; (b) the detailed characterization of an algebra of spatial operators closely inspired, in its scope and structure, by the Schneider-Guting ROSE algebra (i.e., one that is based on a discrete underlying geometry) over the geometries representable by the framework above; (c) distributed in-network algorithms for the operations in the spatial algebra over the representable geometries, thereby enabling (i) new geometries to be derived from induced and asserted ones, and (ii)topological relationships between geometries to be identified; (d) an algorithmic strategy for the evaluation of complex algebraic expressions that is divided into logically-cohesive components; (e) the development of a task processing system that each node is equipped with, thereby with allowing users to evaluate tasks on nodes; and (f) an empirical performance study of the resulting system.
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Christakos, Constantine Kleomenis 1974. "Distributed-in/ distributed-out sensor networks : a new framework to analyze distributed phenomena." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/34183.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2006.Includes bibliographical references (p. 155-165).
With a new way of thinking about organizing sensor networks, we demonstrate that we can more easily deploy and program these networks to solve a variety of different problems. We describe sensor networks that can analyze and actuate distributed phenomena without a central coordinator. Previous implementations of sensor networks have approached the problem from the perspective of centralized reporting of distributed events. By contrast, we create a system that allows users to infer the global state from within the sensor network itself, rather than by accessing an outside, central middleware layer. This is accomplished via dynamic creation of clusters of nodes based on application or intent, rather than proximity. The data collected and returned by these clusters is returned directly to the inquirer at his current location. By creating this Distributed-in/Distributed-out (DiDo) system that bypasses a middleware layer, our networks have the principal advantage of being easily configurable and deployable. We show that a system with this structure can solve path problems in a random graph. These graph problems are directly applicable to real-life applications such as discovering escape routes for people in a building with changing pathways. We show that the system is scalable, as reconfiguration requires only local communication.
(cont.) To test our assumptions, we build a suite of applications to create different deployment scenarios that model the physical world and set up simulations that allow us to measure performance. Finally, we create a set of simple primitives that serve as a high-level organizing protocol. These primitives can be used to solve different problems with distributed sensors, regardless of the underlying network protocols. The instructions provided by the sensors result in tangible performance improvements when the sensors' instructions are directed to agents within a simulated physical world.
by Constantine Kleomenis Christakos.
Ph.D.
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Tewatia, Rohit. "Security in Distributed Embedded Systems." Thesis, Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-1379.
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Communication in a sensor network needs guaranteed reception of data without fail and providing security to it. The authenticity and confidentiality of the data has to be ensured as sensors have limited hardware resources as well as the bandwidth. This thesis addresses the security aspects in wireless sensor networks. The main task of the project is to identify the critical security parameters for these distributed embedded systems. The sensors have extremely limited resources: small amount of memory, low computation capability and poor bandwidth. For example, a sensor platform can have 8KB of flash memory, a 4MHz 8-bit Atmel processor, and a 900MHz radio interface. Various security threats posed to these small wireless sensor networks has been made and solutions proposed. Secure communication between these communicating partners is to be achieved using cryptography.
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Naik, Udayan Lim Alvin S. "Implementation of distributed composition service for self-organizing sensor networks." Auburn, Ala., 2005. http://repo.lib.auburn.edu/2005%20Fall/Thesis/NAIK_UDAYAN_28.pdf.
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Myers, Robert L. "SMART SENSORS VS DISTRIBUTED DATA ACQUISITION." International Foundation for Telemetering, 2001. http://hdl.handle.net/10150/606371.
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International Telemetering Conference Proceedings / October 22-25, 2001 / Riviera Hotel and Convention Center, Las Vegas, NevadaDistributed processing is coming to data acquisition. The desire for smart sensors that can preprocess data, is growing. Making sensors themselves intelligent will reverse the historic trend toward smaller and cheaper sensors. Incorporating current sensor technology into data acquisition nodes in a network will create a distributed data acquisition, DAQ, environment that can acquire data from around the world over the Internet. The future is now.
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Nurellari, Edmond. "Distributed detection and estimation in wireless sensor networks : resource allocation, fusion rules, and network security." Thesis, University of Leeds, 2017. http://etheses.whiterose.ac.uk/17669/.
Full textAbstract:
This thesis addresses the problem of detection of an unknown binary event. In particular, we consider centralized detection, distributed detection, and network security in wireless sensor networks (WSNs). The communication links among SNs are subject to limited SN transmit power, limited bandwidth (BW), and are modeled as orthogonal channels with path loss, flat fading and additive white Gaussian noise (AWGN). We propose algorithms for resource allocations, fusion rules, and network security. In the first part of this thesis, we consider the centralized detection and calculate the optimal transmit power allocation and the optimal number of quantization bits for each SN. The resource allocation is performed at the fusion center (FC) and it is referred as a 'centralized' approach. We also propose a novel fully 'distributed' algorithm to address this resource allocation problem. What makes this scheme attractive is that the SNs share with their neighbors just their individual transmit power at the current states. Finally, the optimal soft fusion rule at the FC is derived. But as this rule requires a-priori knowledge that is difficult to attain in practice, suboptimal fusion rules are proposed that are realizable in practice. The second part considers a fully distributed detection framework and we propose a two-step distributed quantized fusion rule algorithm where in the first step the SNs collaborate with their neighbors through error-free, orthogonal channels. In the second step, local 1-bit decisions generated in the first step are shared among neighbors to yield a consensus. A binary hypothesis testing is performed at any arbitrary SN to optimally declare the global decision. Simulations show that our proposed quantized two-step distributed detection algorithm approaches the performance of the unquantized centralized (with a FC) detector and its power consumption is shown to be 50% less than the existing (unquantized) conventional algorithm. Finally, we analyze the detection performance of under-attack WSNs and derive attacking and defense strategies from both the Attacker and the FC perspective. We re-cast the problem as a minimax game between the FC and Attacker and show that the Nash Equilibrium (NE) exists. We also propose a new non-complex and efficient reputation-based scheme to identify these compromised SNs. Based on this reputation metric, we propose a novel FC weight computation strategy ensuring that the weights for the identified compromised SNs are likely to be decreased. In this way, the FC decides how much a SN should contribute to its final decision. We show that this strategy outperforms the existing schemes.
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Heo, Nojeong Varshney Pramod K. "Distributed deployment algorithms for mobile wireless sensor networks." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2004. http://wwwlib.umi.com/cr/syr/main.
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Fabeck, Gernot [Verfasser]. "Distributed Detection in Wireless Sensor Networks / Gernot Fabeck." Aachen : Shaker, 2011. http://d-nb.info/1098040872/34.
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Liu, Bin. "Channel aware distributed detection in wireless sensor networks." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2006. http://proquest.umi.com/login?COPT=REJTPTU0NWQmSU5UPTAmVkVSPTI=&clientId=3739.
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Jallad, A. H. M. "Distributed computing in space-based wireless sensor networks." Thesis, University of Surrey, 2008. http://epubs.surrey.ac.uk/773025/.
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This thesis investigates the application of distributed computing in general and wireless sensor networks in particular to space applications. Particularly, the thesis addresses issues related to the design of "space-based wireless sensor networks" that consist of ultra-small satellite nodes flying together in close formations. The design space of space-based wireless sensor networks is explored. Consequently, a methodology for designing space-based wireless sensor networks is proposed that is based on a modular architecture. The hardware modules take the form of 3-D Multi-Chip Modules (MCM). The design of hardware modules is demonstrated by designing a representative on-board computer module. The onboard computer module contains an FPGA which includes a system-on-chip architecture that is based on soft components and provides a degree of flexibility at the later stages of the design of the mission.
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Zhou, Yilun. "Fault detection and distributed estimation with sensor networks." Thesis, Imperial College London, 2017. http://hdl.handle.net/10044/1/61021.
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A sensor network is a distributed system, consisting of plenty of embedded sensors that can be deployed over a large-scale physical environment. One of the major applications of sensor networks is to monitor the state of systems that are evolving in the sensing field. Thanks to the emergence of advancements in high-performance processors, nodes in a sensor network can not only collect measurements but coordinate to estimate the state of systems as well. This thesis proposes a monitoring architecture, where distributed state estimation and fault detection algorithms are implemented by every node in the sensor networks to track the system’s state while simultaneously detecting the faults occurred in either the monitored systems or the sensor networks. Several approaches for different monitoring tasks are presented in this thesis and classified into two main parts: distributed state estimation and fault detection algorithms in the monitoring architecture. In the first part, we present two distributed state estimation algorithms in the sensor networks for the monitoring of a system, which can be described by a centralized, decentralized, or distributed dynamic model. The first one is implemented over a sensor network, where the local estimator in each node consists of a filtering step – which uses a weighted combination of neighboring sensors information – and a model-based state predictor. The filtering weights and prediction parameters jointly minimize both the mean and variance of the prediction error in a Pareto optimization framework at each time step. Since each predictor uses the model of the whole system monitored by the sensor network, the algorithm over a sensor network can only monitor a centralized system or each subsystem of a decentralized system. For a distributed system, where several subsystems interact with each other, the second algorithm implemented over several sensor networks is introduced so that each sensor network can coordinate with neighboring networks to monitor the corresponding subsystem of the distributed system. The second part of the thesis is devoted to fault detection algorithms for process faults in monitored systems and sensor faults in sensor networks. The aforementioned estimation algorithm over a sensor network is applied to design process fault detection algorithm for a centralized or decentralized system. A residual is defined, and suitable stochastic thresholds are designed, allowing to set the parameters so to guarantee an upper bound of false alarms probability. For detecting sensor faults in the sensor networks, the centralized, decentralized, and distributed sensor fault detection schemes are proposed in a discrete-time framework. And the detection performance is compared by an industrial benchmark simulation in a continuous stirred tank heater (CSTH) pilot plant. Then a rigorous fault detectability and detection time interval analysis of the centralized sensor fault detection scheme is presented. The performance of proposed distributed estimation methods and effectiveness of presented fault detection methods are evaluated by extensive numerical and industrial benchmark simulations.
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Tang, Zuoyin. "Distributed source coding schemes for wireless sensor networks." Thesis, University of Bath, 2007. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.487519.
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Recent advances in micro-electro-mechanical systems (MEMS) fabrication have made it possible to construct miniature devices containing an embedded system with strong computing capabilities. New generations of low cost sensor nodes can be created small with powerful computing and sensing capabilities. The small sensor nodes together with distributed wireless networking techniques enable the creation of innovative self-organized and peer-to-peer large scale wireless sensor networks (WSNs). A coordinated network of sensor nodes can perform distributed sensing of environmental phenomena over large-scale physical spaces and enable reliable monitoring and control in various applications. WSNs provide bridges between the virtual world of information technology and the real physical world. They represent a fundamental paradigm shift from traditional inter-human personal communications to autonomous inter-device communications. This thesis investigates the problems of target detection and tracking in WSNs. WSNs have some unique advantages over traditional sensor networks. However, the severe scarcity of power, communication and computation resources imposes some major challenges on the design and applications of distributed protocols for WSNs. In particular, this thesis focuses on two aspects of remote target detection and tracking in WSNs: distributed source coding (DSC) and sensor node localization. The primary purpose is to improve the application performance while minimizing energy consumption and bandwidth overhead.
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Lifton, Joshua Harlan 1976. "Pushpin computing : a platform for distributed sensor networks." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/61859.
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Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2002.Includes bibliographical references (p. 169-172).
A hardware and software platform has been designed and implemented for modeling, testing, and deploying distributed peer-to-peer sensor networks comprised of many identical nodes. Each node possesses the tangible affordances of a commonplace pushpin to meet ease-of-use and power considerations. The sensing, computational, and communication abilities of a "Pushpin", as well as a "Pushpin" operating system supporting mobile computational processes are treated in detail. Example applications and future work are discussed.
by Joshua Harlan Lifton.
S.M.
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Leinonen, M. (Markus). "Distributed compressed data gathering in wireless sensor networks." Doctoral thesis, Oulun yliopisto, 2018. http://urn.fi/urn:isbn:9789526220451.
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Abstract Wireless sensor networks (WSNs) consisting of battery-powered sensors are increasingly deployed for a myriad of Internet of Things applications, e.g., environmental, industrial, and healthcare monitoring. Since wireless access is typically the main contributor to battery usage, minimizing communications is crucial to prolong network lifetime and improve user experience. The objective of this thesis is to develop and analyze energy-efficient distributed compressed data acquisition techniques for WSNs. The thesis proposes four approaches to conserve sensors' energy by minimizing the amount of information each sensor has to transmit to meet given application requirements. The first part addresses a cross-layer design to minimize the sensors’ sum transmit power via joint optimization of resource allocation and multi-path routing. A distributed consensus optimization based algorithm is proposed to solve the problem. The algorithm is shown to have superior convergence compared to several baselines. The remaining parts deal with compressed sensing (CS) of sparse/compressible sources. The second part focuses on the distributed CS acquisition of spatially and temporally correlated sensor data streams. A CS algorithm based on sliding window and recursive decoding is developed. The method is shown to achieve higher reconstruction accuracy with fewer transmissions and less decoding delay and complexity compared to several baselines, and to progressively refine past estimates. The last two approaches incorporate the quantization of CS measurements and focus on lossy source coding. The third part addresses the distributed quantized CS (QCS) acquisition of correlated sparse sources. A distortion-rate optimized variable-rate QCS method is proposed. The method is shown to achieve higher distortion-rate performance than the baselines and to enable a trade-off between compression performance and encoding complexity via the pre-quantization of measurements. The fourth part investigates information-theoretic rate-distortion (RD) performance limits of single-sensor QCS. A lower bound to the best achievable compression — defined by the remote RD function (RDF) — is derived. A method to numerically approximate the remote RDF is proposed. The results compare practical QCS methods to the derived limits, and show a novel QCS method to approach the remote RDFTiivistelmä Patterikäyttöisistä antureista koostuvat langattomat anturiverkot yleistyvät esineiden internetin myötä esim. ympäristö-, teollisuus-, ja terveydenhoitosovelluksissa. Koska langaton tiedonsiirto kuluttaa merkittävästi energiaa, kommunikoinnin minimointi on elintärkeää pidentämään verkon elinikää ja parantamaan käyttäjäkokemusta. Väitöskirjan tavoitteena on kehittää ja analysoida energiatehokkaita hajautettuja pakattuja datankeruumenetelmiä langattomiin anturiverkkoihin. Työssä ehdotetaan neljä lähestymistapaa, jotka säästävät anturien energiaa minimoimalla se tiedonsiirron määrä, mikä vaaditaan täyttämään sovelluksen asettamat kriteerit. Väitöskirjan ensimmäinen osa tarkastelee protokollakerrosten yhteissuunnittelua, jossa minimoidaan anturien yhteislähetysteho optimoimalla resurssiallokaatio ja monitiereititys. Ratkaisuksi ehdotetaan konsensukseen perustuva hajautettu algoritmi. Tulokset osoittavat algoritmin suppenemisominaisuuksien olevan verrokkejaan paremmat. Loppuosat keskittyvät harvojen lähteiden pakattuun havaintaan (compressed sensing, CS). Toinen osa keskittyy tila- ja aikatasossa korreloituneen anturidatan hajautettuun keräämiseen. Työssä kehitetään liukuvaan ikkunaan ja rekursiiviseen dekoodaukseen perustuva CS-algoritmi. Tulokset osoittavat menetelmän saavuttavan verrokkejaan korkeamman rekonstruktiotarkkuuden pienemmällä tiedonsiirrolla sekä dekoodausviiveellä ja -kompleksisuudella ja kykenevän asteittain parantamaan menneitä estimaatteja. Työn viimeiset osat sisällyttävät järjestelmämalliin CS-mittausten kvantisoinnin keskittyen häviölliseen lähdekoodaukseen. Kolmas osa käsittelee hajautettua korreloitujen harvojen signaalien kvantisoitua CS-havaintaa (quantized CS, QCS). Työssä ehdotetaan särön ja muuttuvan koodinopeuden välisen suhteen optimoiva QCS-menetelmä. Menetelmällä osoitetaan olevan verrokkejaan parempi pakkaustehokkuus sekä kyky painottaa suorituskyvyn ja enkooderin kompleksisuuden välillä mittausten esikvantisointia käyttäen. Neljäs osa tutkii informaatioteoreettisia, koodisuhde-särösuhteeseen perustuvia suorituskykyrajoja yhden anturin QCS-järjestelmässä. Parhaimmalle mahdolliselle pakkaustehokkuudelle johdetaan alaraja, sekä kehitetään menetelmä sen numeeriseen arviointiin. Tulokset vertaavat käytännön QCS-menetelmiä johdettuihin rajoihin, ja osoittavat ehdotetun QCS-menetelmän saavuttavan lähes optimaalinen suorituskyky
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Jingjing, Hao. "Distributed sensor fault detection and isolation over wireless sensor network." Doctoral thesis, Universite Libre de Bruxelles, 2017. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/254423.
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Wireless sensor networks (WSNs) can provide new methods for information gathering for a variety of applications. In order to ensure the network quality of service, the quality of the measurements has to be guaranteed. Distributed fault detection and isolation schemes are preferred to centralized solutions to diagnose faulty sensors in WSNs. Indeed the first approach avoids the need for a central node that collects information from every sensor node, and hence it limits complexity and energy cost while improving reliability.In the case of state estimation over distributed architectures, the sensor faults can be propagated in the network during the information exchanging process. To build a reliable state estimate one has to make sure that the measurements issued by the different sensors are fault free. That is one of the motivations to build a distributed fault detection and isolation (FDI) system that generates an alarm as soon as a measurement is subject to a fault (has drift, cdots ). In order to diagnose faults with small magnitude in wireless sensor networks, a systematic methodology to design and implement a distributed FDI system is proposed. It resorts to distinguishability measures to indicate the performance of the FDI system and to select the most suitable node(s) for information exchange in the network with a view to FDI. It allows one to determine the minimum amount of data to be exchanged between the different nodes for a given FDI performance. In this way, the specifications for FDI can be achieved while the communication and computation cost are kept as small as possible. The distributed FDI systems are designed both in deterministic and stochastic frameworks. They are based on the parity space approach that exploits spacial redundancy as well as temporal redundancy in the context of distributed schemes. The decision systems with the deterministic method and the stochastic method are designed not only to detect a fault but also to distinguish which fault is occurring in the network. A case study with a WSN is conducted to verify the proposed method. The network is used to monitor the temperature and humidity in a computer room. The distributed FDI system is validated both with simulated data and recorded data.Doctorat en Sciences de l'ingénieur et technologie
info:eu-repo/semantics/nonPublished
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Petersen, Sigmund Seehuus. "Distributed source coding in sensor networks : A practical implementation." Thesis, Norwegian University of Science and Technology, Department of Electronics and Telecommunications, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8705.
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In this thesis we take a closer look at wireless sensor networks and source coding. A necessary condition for this work to have any meaning is that the sensors in the network are spatially co-located and that there is correlation between the data the sensors observe. When there is correlation, there is redundancy in the information communicated that can be removed by source coding techniques. This can be done by emph{distributed source coding}. Slepian and Wolf showed theoretically that there is no rate loss no matter if the sensors are communicating. cite{slepian73} Wyner and Ziv expanded this from the lossless case of Slepian and Wolf to apply to lossy source coding. cite{wyner76} Pradhan and Ramchandran found a practical implementation for the theory of Slepian-Wolf and Wyner-Ziv based on channel coding principles. cite{pradhan03} This can be done because the correlation between any two sources can be modelled as a channel with an error probability. We build our work on their ideas. The channel coding technique we have found most advantageous for this scheme is emph{Low Density Parity-Check} coding. LDPC coding is the most advanced form of linear block coding up to date. It is represented by a sparse parity-check matrix. While LDPC coding in the traditional sense is used for bandwidth expansion of the source to protect it from channel errors, it is used for bandwidth compression, or rate reduction, in the distributed sense. The distributed LDPC scheme is used on medical ECG data as an example. Due to lack of time and the comprehensive task, the adpapted message-passing decoding algorithm needed to fulfill the implementation could not be finished. We have illustrated the distributed encoder system with a $(7,4)$-Hamming code to give an example. The performance of this system is not good enough for any practical use, but will function as a guideline for possible future work in the area.
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Bielefeld, Daniel [Verfasser]. "Ultra-Wideband Sensor Networks for Distributed Detection / Daniel Bielefeld." Aachen : Shaker, 2011. http://d-nb.info/1070152587/34.
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Eriksson, Emil. "Distributed Processing of Visual Features in Wireless Sensor Networks." Licentiate thesis, KTH, Nätverk och systemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-207094.
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As digital cameras are becoming both cheaper and more advanced, they are also becoming more common both as part of hand-held and consumer devices, and as dedicated surveillance devices. The still images and videos collected by these cameras can be used as input to computer vision algorithms for performing tracking, scene understanding, navigation, etc. The performance of such computer vision tasks can be improved by having multiple cameras observing the same events. However, large scale deployment of camera networks is difficult in areas without access to infrastructure for providing power and network connectivity. In this thesis we consider the use of a network of camera equipped sensor nodes as a cost efficient alternative to conventional camera networks. To overcome the computational limitations of the sensor nodes, we enhance the sensor network with dedicated processing nodes, and process images in parallel using multiple processing nodes. In the first part of the thesis, we formulate the minimization problem of the time required from image capture until the visual features are extracted from the image. The solution to the minimization problem is an allocation of sub-areas of a captured image to a subset of the processing nodes, which perform the feature extraction. We use the temporal correlation of the image contents to predict an approximation of the distribution of visual features in a captured image. Based on the approximate distribution, we compute an approximate solution to the minimization problem using linear programming. We show that the last value predictor gives a good trade-off between performance and computational complexity. In the second part of the thesis, we propose fully distributed algorithms for allocation of image sub-areas to the processing nodes in a multi-camera Visual Sensor Network. The algorithms differ in the amount of information available and in how allocation updates are applied. We provide analytical results on the existence of equilibrium allocations, and show that an equilibrium allocation may not be optimal. We show that fully distributed algorithms are most efficient when sensors make asynchronous changes to their allocations, and in topologies with less symmetry. However, with the addition of sparse coordination, both average and worst-case performance can be improved significantly.Allt eftersom digitalkameror blir både billigare och mer avancerade blir de också vanligare i handhållna enheter, i hemelektronik och som dedikerad övervakningsutrustning. Algoritmer för datorseende kan användas på stillbilderna och videoklippen som samlas in av dessa kameror för objektidentifiering, scenförståelse, navigering, mm. Genom att använda data från flera kameror som observerar samma händelser kan prestandan hos dessa datorseendealgoritmer förbättras. Utplacering av kameranätverk är emellertid svårt i områden utan tillgång till infrastruktur som kan tillhandahålla elektricitet och nätverksanslutning. I denna avhandling studerar vi nätverk av kamerautrustade sensornoder som ett kostnadseffektivt alternativ till konventionella kameranätverk. För att övervinna beräkningsbegränsningarna hos sensornoderna förstärker vi sensornätverket med dedikerade beräkningsnoder och bearbetar bilder parallellt i flera beräkningsnoder. I den första delen av avhandlingen formulerar vi minimeringsproblemet för den tid som krävs från bildupptagning tills en representation av den visuella informationen extraheras från bilden. Lösningen till minimeringsproblemet är en fördelning av delområden av en infångad bild till en delmängd av beräkningsnoderna. Beräkningsnoderna bearbetar bilderna för att ta fram representationen av den visuella informationen. Vi använder den tidsmässiga korrelationen av bildinnehållet för att förutsäga en approximation av fördelningen av visuell information i en infångad bild. Baserat på den ungefärliga fördelningen beräknar vi en approximativ lösning på minimeringsproblemet med hjälp av linjärprogrammering. Vi visar att det går att får en bra kompromiss mellan prestanda och beräkningskomplexitet genom att använda det visuella innehållet i tidigare bildrutor för att förutsäga innehållet i kommande bildrutor. I den andra delen av avhandlingen föreslår vi helt distribuerade algoritmer för tilldeling av delar av bilder till beräkningsnoder i ett visuellt sensornätverk. Algoritmerna skiljer sig i mängden tillgänglig information och hur uppdateringar av tilldelningar verkställs. Vi tillhandahåller analytiska resultat för förekomsten av jämviktstilldelningar och visar att en given jämviktstilldelning inte nödvändigtvis är optimal. Vi visar även att fullt distribuerade algoritmer är mest effektiva när sensornoder gör asynkrona förändringar i sina tilldelningar och i mindre symmetriska topologier. Genom att lägga till gles koordination kan prestandan förbättras avsevärt både i genomsnitt och i värsta fall.
QC 20170516
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Papalexidis, Nikolaos. "Distributed algorithms for beamforming in wirless [sic] sensor networks." Thesis, Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion-image.exe/07Jun%5FPapalexidis.pdf.
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Thesis (Electrical Engineer and M.S. in Electrical Engineering)--Naval Postgraduate School, June 2007.Thesis Advisor(s): Murali Tummala, John C. McEachen. "June 2007." Includes bibliographical references (p. 111-113). Also available in print.
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Ing, Garrick. "Distributed particle filters for object tracking in sensor networks." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=98971.
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A particle filter (PF) is a simulation-based algorithm used to solve estimation problems, such as object tracking. The PF works by maintaining a set of "particles" as candidate state descriptions of an object's position. The filter determines how well the set of particles describe the observations and fit the dynamic model, in order to form an object state estimate. The drawback of the basic PF is that the algorithm functions by collecting all data at a fusion centre. This leads to high communication and energy costs in a resource-limited network such as the sensor network. In this thesis, we analyze the PF to determine how it can be modified for efficient use in a sensor network. Our main priority is to keep communication and energy costs low since this increases the network lifetime. We propose two innovative particle filtering algorithms which minimizes the associated costs.
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Nabeel, Mohammed M. [Verfasser]. "Reliable communication in distributed sensor networks / Mohammed M. Nabeel." Paderborn : Universitätsbibliothek, 2019. http://d-nb.info/1183087837/34.
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MILLER, TAMARA GUERRA. "DISTRIBUTED SPARSITY-AWARE SIGNAL PROCESSING ALGORITHMS FOR SENSOR NETWORKS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2016. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=27190@1.
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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIROCOORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE EXCELENCIA ACADEMICA
Neste trabalho de dissertação são propostos algoritmos adaptativos que exploram a esparsidade em redes distribuídas de sensores para estimação de parâmetros e estimação espectral. São desenvolvidos algoritmos gradiente conjugado (CG) distribuído para os protocolos consenso e difusão em versão convencional e modificada (MCG). Esses algoritmos são desenvolvidos com exploração de esparsidade usando as funções penalidades l1 e log-sum. Os métodos propostos apresentam um melhor desempenho en termos de velocidade de convergência e desvio médio quadratico (MSD) que as já conhecidas variantes distribuídas do algoritmo least mean square (LMS) e muito próximo ao desempenho do algoritmo recursive least square (RLS). Além disso, propõe-se um algoritmo distribuído de optimização alternada de variáveis discretas e contínuas (DAMDC) baseado no LMS. O algoritmo DAMDC-LMS apresenta um desempenho muito próximo ao algoritmo oráculo e tem maior velocidade de convergência que os algoritmos estudados com exploração de esparsidade. Os resultados numéricos mostram que o algoritmo DAMDC-LMS pode ser aplicado em vários cenários.
This dissertation proposes distributed adaptive algorithms exploiting sparsity for parameter and spectrum estimation over sensor networks. Conventional and modified conjugate gradient (CG and MCG) algorithms using consensus and diffusion strategies are presented. Sparsity-aware versions of CG an MCG algorithms using l1 and log-sum penalty functions are developed. The proposed sparsity-aware and non-sparse CG and MCG methods outperform the equivalent variants of the least-mean square (LMS) algorithms in terms of convergence rate and mean square deviation (MSD) at steady state, and have a close performance to the recursive least square (RLS) algorithm. The diffusion CG strategies have shown the best performance, specifically the adapt then combine (ATC) version. Furthermore a distributed alternating mixed discretecontinuous (DAMDC) algorithm to approach the oracle algorithm based on the diffusion strategy for parameter and spectrum estimation over sensor networks is proposed. An LMS type algorithm with the DAMDC proposed technique obtains the oracle matrix in an adaptive way and compare it with the existing sparsity-aware as well as the classical algorithms. The proposed algorithm has an improved performance in terms of MSD. Numerical results show that the DAMDC-LMS algorithm is reliable and can be applied in several scenarios.
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Chachra, Sumit, and Theodore Elhourani. "RESOURCE ALLOCATION IN SENSOR NETWORKS USING DISTRIBUTED CONSTRAINT OPTIMIZATION." International Foundation for Telemetering, 2004. http://hdl.handle.net/10150/605299.
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International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, CaliforniaSeveral algorithms have been proposed for solving constraint satisfaction and the more general constraint optimization problem in a distributed manner. In this paper we apply two such algorithms to the task of dynamic resource allocation in the sensor network domain using appropriate abstractions. The aim is to effectively track multiple targets by making the sensors coordinate with each other in a distributed manner, given a probabilistic representation of tasks (targets). We present simulation results and compare the performance of the DBA and DSA algorithms under varying experimental settings.
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Anilkumar, Ravi. "Energy-Efficient Measurement of Coverage in Distributed Sensor Networks." Thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/9787.
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Large-scale sensor networks have become a reality due to recent developments in sensor node hardware and algorithms. Sensor networks can provide real-time information based on detection and tracking. This information cannot be reliable if little is known about the sensor coverage of the network, which can be defined as the total sensing range of the network due to contributions from each sensor node. Knowledge about coverage can also be useful in determining if there is any gap in coverage in the region of interest as well as improving the algorithm that determines the placement of nodes. Although coverage estimation is this thesis's central concern, other factors such as energy-efficiency and network lifespan that affect the network performance are investigated. Energy-efficiency and network lifespan depend on the communication model used for obtaining coverage information from each sensor node. This thesis proposes the use of B-splines for describing coverage efficiently. The properties of B-splines also enable communication models such as directed diffusion and hierarchical clustering to provide better performance as compared to a centralized scheme. Results obtained from simulation experiments indicate that hierarchical clustering and directed diffusion can be used effectively for coverage measurement. The hierarchical clustering model, however, exhibited some drawbacks such as a dependency on the routing scheme and poor node-failure recovery.Master of Science
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Whipps, Gene Thomas. "Contributions to Distributed Detection and Estimation over Sensor Networks." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1502970194073045.
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Muralidharan, Gautam. "On the distributed revocation of nodes in sensor networks." College Park, Md. : University of Maryland, 2004. http://hdl.handle.net/1903/164.
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Thesis (M.S.) -- University of Maryland, College Park, 2004.Thesis research directed by: Dept. of Electrical and Computer Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Krishnan, Rajet. "Problems in distributed signal processing in wireless sensor networks." Thesis, Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/1351.
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Yu, Jia. "Distributed parameter and state estimation for wireless sensor networks." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28929.
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The research in distributed algorithms is linked with the developments of statistical inference in wireless sensor networks (WSNs) applications. Typically, distributed approaches process the collected signals from networked sensor nodes. That is to say, the sensors receive local observations and transmit information between each other. Each sensor is capable of combining the collected information with its own observations to improve performance. In this thesis, we propose novel distributed methods for the inference applications using wireless sensor networks. In particular, the efficient algorithms which are not computationally intensive are investigated. Moreover, we present a number of novel algorithms for processing asynchronous network events and robust state estimation. In the first part of the thesis, a distributed adaptive algorithm based on the component-wise EM method for decentralized sensor networks is investigated. The distributed component-wise Expectation-Maximization (EM) algorithm has been designed for application in a Gaussian density estimation. The proposed algorithm operates a component-wise EM procedure for local parameter estimation and exploit an incremental strategy for network updating, which can provide an improved convergence rate. Numerical simulation results have illustrated the advantages of the proposed distributed component-wise EM algorithm for both well-separated and overlapped mixture densities. The distributed component-wise EM algorithm can outperform other EM-based distributed algorithms in estimating overlapping Gaussian mixtures. In the second part of the thesis, a diffusion based EM gradient algorithm for density estimation in asynchronous wireless sensor networks has been proposed. Specifically, based on the asynchronous adapt-then-combine diffusion strategy, a distributed EM gradient algorithm that can deal with asynchronous network events has been considered. The Bernoulli model has been exploited to approximate the asynchronous behaviour of the network. Compared with existing distributed EM based estimation methods using a consensus strategy, the proposed algorithm can provide more accurate estimates in the presence of asynchronous networks uncertainties, such as random link failures, random data arrival times, and turning on or off sensor nodes for energy conservation. Simulation experiments have been demonstrated that the proposed algorithm significantly outperforms the consensus based strategies in terms of Mean-Square- Deviation (MSD) performance in an asynchronous network setting. Finally, the challenge of distributed state estimation in power systems which requires low complexity and high stability in the presence of bad data for a large scale network is addressed. A gossip based quasi-Newton algorithm has been proposed for solving the power system state estimation problem. In particular, we have applied the quasi-Newton method for distributed state estimation under the gossip protocol. The proposed algorithm exploits the Broyden- Fletcher-Goldfarb-Shanno (BFGS) formula to approximate the Hessian matrix, thus avoiding the computation of inverse Hessian matrices for each control area. The simulation results for IEEE 14 bus system and a large scale 4200 bus system have shown that the distributed quasi-Newton scheme outperforms existing algorithms in terms of Mean-Square-Error (MSE) performance with bad data.