Um estudo sobre redes de sensores sem fio

This work aims to study wireless sensor networks and its behavior, pointing out its attributes, application areas and challenges. Are dealt with issues relating to communication, standards used, applications, showing the potential of wireless sensor networks. It is also presented the main differences and similarities between ad-hoc and wireless sensor networks.Esse trabalho tem como objetivo estudar as redes de sensores sem fio e seu comportamento, apontando seus atributos, áreas de aplicação e desafios. São tratadas questões relativas à comunicação, padrões utilizados, aplicação dos sensores, mostrando o potencial das redes de sensores sem fio. Também são apresentadas as diferenças e semelhanças que as redes de sensores sem fio possuem com as redes não estruturadas

Fusão de dados paralela em redes de sensores sem fio densas utilizando algoritmo genético

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-graduação em Engenharia de Automação e SistemasRedes de sensores sem fio são redes que possuem severas restrições computacionais. Após a implantação dessas redes no ambiente, ainda existe o problema de auto-configuração e auto-gerenciamento em virtude da necessidade que se tem dessas redes serem autônomas. Conciliar as restrições computacionais bem como a gerência da estrutura dinâmica dessas redes é uma tarefa difícil. O presente trabalho aborda o uso de algoritmo genético para atingir a auto-configuração e auto-otimização em redes de sensores sem fio densas. Duas abordagens de algoritmo genético foram implementadas e simuladas. Essas abordagens atuam em um nodo central, o qual não possui restrições de recursos. Este nodo é responsável por gerenciar os demais nodos da rede. O objetivo final é reduzir as perdas de mensagens, e melhorar a qualidade dos dados coletados. Como conseqüência, consegue-se aumentar a eficiência energética da rede. Os resultados das simulações demonstraram a viabilidade dessa abordagem. There is a considerable computational limitation for running Wireless Sensor network. After its implantation into an environment, those networks still expose problems to be solve, e.g. autonomic self-configuring and self-management issues. Therefore, conciliating computational restrictions and networks structure management is a challenge. The present work concerns the use of genetic algorithm to obtain self-configuring and self-optimization goals in dense wireless networks sensors. Two genetic algorithms approaches were implemented and simulated. Those approaches ran into a non resource-constrained central node. This node was the responsible to manage every other node at the networks. The main objective was to reduce the lost of messages, and also improve the quality of the collected data. As consequence, the energetic efficiency of the network meant to be increased. As results of simulations it was demonstrated that this approach is viable

Stealthy attacks and defense strategies in competing sensor networks

The fundamental objective of sensor networks underpinning a variety of applications is the collection of reliable information from the surrounding environment. The correctness of the collected data is especially important in applications involving societal welfare and safety, in which the acquired information may be utilized by end-users for decision-making. The distributed nature of sensor networks and their deployment in unattended and potentially hostile environments, however, renders this collection task challenging for both scalar and visual data. In this work we propose and address the twin problem of carrying out and defending against a stealthy attack on the information gathered by a sensor network at the physical sensing layer as perpetrated by a competing hostile network. A stealthy attack in this context is an intelligent attempt to disinform a sensor network in a manner that mitigates attack discovery. In comparison with previous sensor network security studies, we explicitly model the attack scenario as an active competition between two networks where difficulties arise from the pervasive nature of the attack, the possibility of tampering during data acquisition prior to encryption, and the lack of prior knowledge regarding the characteristics of the attack. We examine the problem from the perspective of both the hostile and the legitimate network. The interaction between the networks is modeled as a game where a stealth utility is derived and shown to be consistent for both players in the case of stealthy direct attacks and stealthy cross attacks. Based on the stealth utility, the optimal attack and defense strategies are obtained for each network. For the legitimate network, minimization of the attacker’s stealth results in the possibility of attack detection through established paradigms and the ability to mitigate the power of the attack. For the hostile network, maximization of the stealth utility translates into the optimal attack avoidance. This attack avoidance does not require active communication among the hostile nodes but rather relies on a level of coordination which we quantify. We demonstrate the significance and effectiveness of the solution for sensor networks acquiring scalar and multidimensional data such as surveillance sequences and relate the results to existing image sensor networks. Finally we discuss the implications of these results for achieving secure event acquisition in unattended environments