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Doctoral Thesis
DOI
10.11606/T.3.2017.tde-07022017-111104
Document
Author
Full name
Marcel Stefan Wagner
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2016
Supervisor
Committee
Ramirez, Miguel Arjona (President)
Gabos, Denis
Hernandez, Emílio Del Moral
Kleinschmidt, João Henrique
Lima Filho, Diogo Ferreira
Title in Portuguese
Sistema cognitivo com tomada de decisão baseada em Lógica Fuzzy para aplicação em ambientes de redes de sensores sem fio com múltiplos saltos.
Keywords in Portuguese
Cognição
Controle adaptativo
Lógica Fuzzy
Redes cognitivas
Wireless
Abstract in Portuguese
Esta Tese estuda a implementação de um novo mecanismo de análise e atuação em Redes de Sensores Sem Fio (RSSF) com múltiplos saltos baseado em características de cognição aplicadas aos nós que compõem a rede. Para tanto, é proposto um algoritmo de detecção de variabilidade dos nós sensores, envolvendo movimentação do nó, alcance do sinal da antena do sensor, quantidade de nós que fazem parte da rede e o número de conexões possíveis com nós vizinhos. Além do algoritmo de detecção de variabilidade, propõe-se um sistema multilayer denominado Adaptive Cognitive System (ACS) com base na arquitetura de Cognitive Networks (CN), que abrange: coleta, tratamento e tomada de decisão. O tratamento se refere à parte cognitiva do sistema, contemplando a criação do Cognitive Processor Module (CPMod), que por sua vez, abrange a semântica da rede, aplicação de Lógica Fuzzy e interação com um simulador de Wireless Sensor Networks (WSN) e a tomada de decisão é realizada pelo CPMod com base no resultado de análises executadas em rounds e histórico da rede com o uso de funções de pertinência de fuzzificação e defuzzificação, regras Fuzzy e inferência sobre informações coletadas da rede. Observou-se com os testes realizados na rede, utilizando-se o algoritmo de detecção, que a variabilidade dos nós sensores afeta diretamente o desempenho da rede, devido à necessidade de reestabelecimento de links e rotas entre os nós. Através de testes realizados via software na WSN, identificou-se que com o uso do ACS houve melhora significativa no desempenho em relação ao atraso fim-a-fim, latência, quantidade de pacotes descartados e de energia consumida pelos nós na rede. O ACS demonstrou potencial para a solução de problemas relacionados com as métricas destacadas, realizando ajustes em múltiplas camadas de rede do padrão IEEE 802.15.4 para até 200 nós na rede.
Title in English
Cognitive system with decision making based on Fuzzy Logic applied to multi-hop wireless sensor networks.
Keywords in English
Adaptive system
Cognition
Cognitive networks
Fuzzy Logic
Wireless
Abstract in English
This Dissertation examines the implementation of a mechanism to analyze and act on multi-hop Wireless Sensor Networks (WSN) with the use of cognitive features applied to the network nodes. For this purpose, a variation detection algorithm was proposed for monitoring sensor nodes, involving the node's mobility features, signal range of the sensor antenna, the number of nodes in the network and the number of possible connections to neighboring nodes. In addition to the detection algorithm, a multi-layer system is proposed, named Adaptive Cognitive System (ACS). It is based on Cognitive Networks (CN) architecture, including data gathering, information treatment and decision making. The main part of the system is the Cognitive Processor Module (CPMod), which extracts the information about the WSN. In turn the Fuzzy Logic block works in tandem with the semantic engine to feed the codes to CPMod in the decision making process. The codes are the result of analysis performed on rounds using fuzzification and defuzzification membership functions, fuzzy rules and inference over information collected from the network. It was observed in tests performed in the WSN, using the detection algorithm, that the variability in sensor nodes directly affects the network performance due to the effort spent in rerounting links and paths. Through WSN testing performed via software, it was found that using the ACS implies in significant improvement in performance over the end-to-end delay, network latency, dropped packets and amount of energy consumed by nodes on the network. The ACS potential is proven for solving problems related to the previously mentioned metrics, performing adjustments on multiple network layers standardized by IEEE 802.15.4 up to 200 nodes in the network.
 
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Publishing Date
2017-02-07
 
WARNING: The material described below relates to works resulting from this thesis or dissertation. The contents of these works are the author's responsibility.
  • WAGNER, MARCEL STEFAN, Ramirez, Miguel Arjona, and ZUCCHI, WAGNER LUIZ. Adaptive Cognitive System Applied on Wireless Sensor Networks Nodes Decisions [doi:10.1109/CSNT.2015.65]. In 2015 Fifth International Conference on Communication Systems and Network Technologies (CSNT), Gwalior. 2015 Fifth International Conference on Communication Systems and Network Technologies. : IEEE, 2015.
All rights of the thesis/dissertation are from the authors
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