Wireless sensor networks have many sensor devices that send their data to the sink or base station for further processing. This is called direct delivery. But this leads to heavy traffic in the network and as the nodes are limited with energy, this decreases the lifetime of the network. So data aggregation technique is introduced to improve the lifetime. This technique aggregates or merges the multiple incoming packets in to single packet and forwards it to sink. There is different data aggregation techniques based on the topology of the network. This report clearly explains the purpose of data aggregation and gathering in WSN, data aggregation in flat networks and data aggregation in hierarchical networks, different data aggregation techniques in cluster based networks, chain based, tree based and grid based networks. Data aggregation technique can successfully minimize the data traffic and energy consumption only when it is carried out in a secure manner. Part2 of the survey explains the possible attacks that affect data aggregation in wireless sensor network. The secure data aggregation techniques in wireless sensor networks are also discussed in this report.

Submitted by Geyciane Santos (geyciane_thamires@hotmail.com) on 2015-08-06T14:07:38Z No. of bitstreams: 1 Dissertação - Isabel Cristina Souza Dinóla.pdf: 562066 bytes, checksum: fb6aeda0c4854690f169abad1c217b8d (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-08-07T13:20:19Z (GMT) No. of bitstreams: 1 Dissertação - Isabel Cristina Souza Dinóla.pdf: 562066 bytes, checksum: fb6aeda0c4854690f169abad1c217b8d (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-08-07T13:24:35Z (GMT) No. of bitstreams: 1 Dissertação - Isabel Cristina Souza Dinóla.pdf: 562066 bytes, checksum: fb6aeda0c4854690f169abad1c217b8d (MD5) / Made available in DSpace on 2015-08-07T13:24:35Z (GMT). No. of bitstreams: 1 Dissertação - Isabel Cristina Souza Dinóla.pdf: 562066 bytes, checksum: fb6aeda0c4854690f169abad1c217b8d (MD5) Previous issue date: 2009-05-22 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The phase diagram of the two-dimensional super-antiferromagnetic (SAF) Ising model in the presence of a magnetic field is investigated within the framework of a real-space renormalization-group approximation. We consider nearest neighbor ferromagnetic interactions along the x(y) direction and antiferromagnetic interactions in the y(x) direction. The system presents a ordered phase at low temperatures and zero fields. The presence of a magnetic field induces a competition between the energy interactions of the SAF Hamiltonian. The resulting behavior has been a matter of controversy in the last years. We depicted the main results in the magnetic field versus temperature phase diagram. A second-order transition line separates a super-antiferromagnetic phase from a field induced ferromagnetic phase. Our study reveals that the magnetic field induces a phase transition at a single temperature value, thus, we did not find any evidence of reentrant behavior as claimed by some authors. / Utilizamos uma técnica de grupo de renormalização no espaço real para estudar o sistema super antiferromagneto (SAF) de Ising bidimensional sob a influência de um campo magnético externo. Neste modelo as interações de primeiros vizinhos na direção x são ferromagnéticas e na direção y são antiferromagnéticas. Este sistema apresenta uma fase ordenada, para baixas temperaturas e campos nulos, com uma estrutura de linhas ferromagnéticas e colunas antiferromagnéticas. A aplicação do campo magnético induz uma competição entre as energias de interação do modelo e o comportamento resultante desta competição tem sido objeto de estudo e gerado algumas controvérsias nos últimos anos. Na presença do campo magnético observa-se, além da fase SAF, a fase ferromagnética induzida pelo campo (FIC). Apresentamos neste trabalho o diagrama de fases completo do sistema SAF no plano temperatura versus campo magnético. O diagrama de fases obtido mostra uma linha de transição de segunda ordem separando a fase SAF da fase FIC. Nossos resultados contrariam resultados anteriores que preveêm um comportamento reentrante no diagrama de fases do sistema SAF.

Made available in DSpace on 2015-04-11T14:02:47Z (GMT). No. of bitstreams: 1 Andre Ricardo Melo Araujo.pdf: 3722790 bytes, checksum: 1876d821e1e927795304f1c1ee7bbb67 (MD5) Previous issue date: 2013-03-01 / FAPEAM - Fundação de Amparo à Pesquisa do Estado do Amazonas / Wireless Sensor Network (WSN) is a special kind of ad hoc networks composed of devices capable of processing, storing, sensing the environment, and transmitting data via wireless communication interface. The sensor nodes have several limitations, among them the capacity of energy because to the reduced size. For this reason, many searches have been done with a view to improving the energy consumption of sensor nodes. This work aims to address the Problem of Coverage, Clustering and Routing with Mobile Sink (PCAR-SM, in portuguese Problema de Cobertura, Agrupamento e Roteamento com Sorvedouro Móvel) in WSN with mobile sink consisting of: given a set of sensor nodes and a monitoring area, develop algorithms to find the best subset of sensor nodes to cover the monitoring area, group them in a smaller number of clusters and find the shortest route to mobile sink navigate. The PCAR-SM is a strategy used to reduce the energy consumption of sensor nodes, data collisions, interference and redundant data in networks with high concentration of sensor nodes per area. The purpose of this paper is to solve each problem separately and together, in order to evaluate the impact of each problem on the other. The Coverage Problem has been solved with two metaheuristics: an Genetic Algorithm (GA) and a Greedy Randomized Adaptive Search Procedure (GRASP) algorithm. In the latter we used two representations of solution: (a) representation by sensor, where each element of the solution vector represents a sensor node that must be switched on or off; (b) representation by demand, where each element of the solution vector represents a demand point will indicate which sensor node cover it. The AG uses only the representation by demand. The computational results for Coverage Problem used the benchmark of Beasley s OR Library and it was possible seen that the GRASP with representation by demand achieved better results than the GA and the GRASP with representation by sensor when the optimization criterion is to minimize the total cost of each sensor node used in the solution. For Clustering Problem was created approach of virtual grids. In this approach, we divide the area into grids and clusters are formed by a set of adjacent grids (maximum 5 grids in group) forming a cross schematic. The aim of the problem is to minimize the number of clusters in the area. With this approach, we can model the Clustering Problem as a Set Cover Problem (SCP) without overlapping (an element does not belong to more than one set), which was treated by a greedy heuristic called Greedy Clustering Algorithm (GCA). The virtual grids proved to be a good solution because it is simple to identify a node which grid it belongs. Its simplicity also makes it a appropriate method for a distributed version. The Routing Problem of sink was modeled as the Travelling Salesman Problem (TSP), where the mobile sink part of a corner of the monitoring area, runs through the area visiting all clusters and returns to the starting point. For this, we propose two greedy approaches based on nearest neighbor, the Routing Greedy Algorithm - Center (RGA-C) and Routing Greedy Algorithm - Border (RGA-B). The route of the sink was also solved by a heuristic based on algorithm Centralized Spatial Partitioning (CSP). In CSP approach, the route is fixed and reminds the movement of a snake. The results show that fixed route produces a path with smaller size compared to the greedy heuristic for TSP. We analyze also the PCAR-SM, creating heuristic strategies. The union of the Clustering Problem and Routing Problem proved more beneficial in relation to the size of the sink s route. The union of Coverage Problem and Clustering Problem only proved beneficial when the communication radius was about 3,9 times greater than the sensing radius. Our results show that solve problems together allows some changes in the algorithms will lead to better results. / As Redes de Sensores Sem Fio (RSSFs) são um tipo especial de redes ad hoc constituídas por dispositivos capazes de processar, armazenar, sensoriar o ambiente e transmitir dados via interface de comunicação sem fio, denominados nós sensores. Os nós sensores possuem várias limitações, dentre elas, a capacidade de energia devido ao tamanho reduzido. Por isto, muitas pesquisas foram feitas tendo em vista a melhoria no consumo de energia dos nós sensores. Este trabalho tem como objetivo tratar o Problema de Cobertura, Agrupamento e Roteamento com Sorvedouro Móvel (PCAR-SM) em RSSF com nó sorvedouro móvel, que consiste em: dado um conjunto de nós sensores e uma área de monitoramento, desenvolver algoritmos para encontrar o melhor subconjunto de nós sensores que cubra a área de monitoramento, juntá-los no menor número de grupos possíveis e encontrar a menor rota para um nó sorvedouro móvel percorrer. O PCAR-SM é uma estratégia utilizada para diminuir o consumo de energia dos nós sensores, a colisão de dados, as interferências e os dados redundantes em redes com alta concentração de nós sensores por área. A proposta deste trabalho é resolver cada problema separadamente e em conjunto, de modo a avaliar o impacto de cada problema na solução do outro. O Problema de Cobertura foi resolvido com duas metaheurísticas: um Algoritmo Genético (AG) e um algoritmo Greedy Randomized Adaptive Search Procedure (GRASP). Neste último foram utilizadas duas representações de solução: (a) representação por sensor, onde cada elemento do vetor de solução representa um nó sensor que estará ligado ou desligado; (b) representação por demanda, onde cada elemento do vetor de solução representa um ponto de demanda no qual indicará qual o nó sensor o cobre. O AG utiliza apenas a representação por demanda. Os resultados computacionais para o Problema de Cobertura utilizaram o benchmark da Beasley s OR Library e foi possível constatar que o GRASP com representação por demanda obteve melhores resultados que o AG e o GRASP com representação por sensor quando o critério de otimização é minimizar a soma total dos custos de cada nó sensor utilizado na solução. Para o Problema de Agrupamento foi criada uma abordagem de grades virtuais. Nesta abordagem dividimos a área em grades e os grupos são formados por um conjunto de grades adjacentes (no máximo 5 grades) formando um esquema de cruz. O objetivo do problema é minimizar o número de grupos na área. A partir desta abordagem, pode-se modelar o Problema de Agrupamento como um Problema de Cobertura de Conjuntos (PCC) sem sobreposição (um elemento não pertence a mais de um conjunto), que foi tratada por uma heurística gulosa denominada Greedy Clustering Algorithm (GCA). Os grades virtuais provou ser uma boa solução por ser simples para um nó identificar a qual grade ele pertence. Sua simplicidade ainda o torna uma método adequado para uma versão distribuída. O Problema de Roteamento do nó sorvedouro foi modelado como o Problema do Caixeiro Viajante (PCV), onde o nó sorvedouro móvel parte de um canto da área de monitoramento, percorre a área visitando todos os grupos e retorna ao ponto inicial. Para isto, propomos duas abordagens gulosas baseadas no vizinho mais próximo, o Routing Greedy Algorithm - Center (RGA-C) e o Routing Greedy Algorithm - Border (RGA-B). A rota do nó sorvedouro também foi resolvida por uma heurística baseada no algoritmo Centralized Spatial Partitioning (CSP). Na abordagem CSP, a rota é fixa e lembra o movimento de uma cobra. Os resultados mostram que a rota fixa gera um percurso com tamanho menor em comparação com as heurísticas gulosas para o PCV. Analisamos, ainda, o PCAR-SM, criando estratégias heurísticas. Aunião dos Problema de Agrupamento e Roteamento, provou ser mais benéfica em relação ao tamanho da rota do nó sorvedouro, já a união do Problema de Cobertura com o Problema de Agrupamento só mostrou ser benéfica quando o raio de comunicação era aproximadamente 3, 9 vezes maior que o raio de sensoriamento. Nossos resultados, mostram que resolver os problemas em conjunto permite que algumas mudanças nos algoritmos levem a melhores resultados.

Menschliche Systeme werden seit einiger Zeit modelliert und analysiert auf der Basis der Theorie komplexer Netzwerke. Dies erlaubt es quantitativ zu untersuchen, welche strukturellen und zeitlichen Merkmale eines Systems Ausbreitungsprozesse beeinflussen, z.B. von Informationen oder von Infektionskrankheiten. Im ersten Teil der Arbeit wird untersucht, wie eine modular-hierarchische Struktur von statischen Netzwerken eine schnelle Verbreitung von Signalen ermöglicht. Es werden neue Heuristiken entwickelt um die Random-Walk-Observablen “First Passage Time” und “Cover Time” auf lokal geclusterten Netzwerken zu ermitteln. Vergleiche mit der Approximation eines gemittelten Mediums zeigen, dass das Auftreten der beobachteten Minima der Observablen ein reiner Netzwerkeffekt ist. Es wird weiterhin dargelegt, dass nicht alle modular-hierarchischen Netzwerkmodelle dieses Phänomen aufweisen. Im zweiten Teil werden zeitlich veränderliche face-to-face Kontaktnetzwerke auf ihre Anfälligkeit für Infektionskrankheiten untersucht. Mehrere Studien belegen, dass Menschen vornehmlich Zeit in Isolation oder kleinen, stark verbundenen Gruppen verbringen, und dass ihre Kontaktaktivität einem zirkadianen Rhythmus folgt. Inwieweit diese beiden Merkmale die Ausbreitung von Krankheiten beeinflussen, ist noch unklar. Basierend auf einem neuen Modell wird erstmals gezeigt, dass zirkadian variierende Netzwerke Trajektorien folgen in einem Zustandsraum mit einer strukturellen und einer zeitlichen Dimension. Weiterhin wird dargelegt, dass mit zunehmender Annäherung der zeitlichen Dimension von System und Krankheit die systemische Infektionsanfälligkeit sinkt. Dies steht in direktem Widerspruch zu Ergebnissen anderer Studien, die eine zunehmende Anfälligkeit vorhersagen, eine Diskrepanz, die auf die Ungültigkeit einer weit verbreiteten Approximation zurückzuführen ist. Die hier vorgestellten Ergebnisse implizieren, dass auf dem Gebiet die Entwicklung neuer theoretischer Methoden notwendig ist. / Human systems have been modeled and analyzed on the basis of complex networks theory in recent time. This abstraction allows for thorough quantitative analyses to investigate which structural and temporal features of a system influence the evolution of spreading processes, such as the passage of information or of infectious diseases. The first part of this work investigates how the ubiquitous modular hierarchical structure of static real-world networks allows for fast delivery of messages. New heuristics are developed to evaluate random walk mean first passage times and cover times on locally clustered networks. A comparison to average medium approximations shows that the emergence of these minima are pure network phenomena. It is further found that not all modular hierarchical network models provide optimal message delivery structure. In the second part, temporally varying face-to-face contact networks are investigated for their susceptibility to infection. Several studies have shown that people tend to spend time in small, densely-connected groups or in isolation, and that their connection behavior follows a circadian rhythm. To what extent both of these features influence the spread of diseases is as yet unclear. Therefore, a new temporal network model is devised here. Based on this model, circadially varying networks can for the first time be interpreted as following trajectories through a newly defined systemic state space. It is further revealed that in many temporally varying networks the system becomes less susceptible to infection when the time-scale of the disease approaches the time-scale of the network variation. This is in direct conflict with findings of other studies that predict increasing susceptibility of temporal networks, a discrepancy which is attributed to the invalidity of a widely applied approximation. The results presented here imply that new theoretical advances are necessary to study the spread of diseases in temporally varying networks.