Uma abordagem para tratamento da desconexão de dispositivos móveis na utilização de recursos de Grif computacional

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-graduação em Ciência da ComputaçãoA utilização de dispositivos móveis em ambientes de grid computacional tem sido explorada para aplicações técnico-científicas, que muitas vezes podem se beneficiar do poder computacional e mobilidade desses ambientes. Todavia, a integração dos dispositivos móveis requer um tratamento mais criterioso de algumas de suas limitações. Uma das vulnerabilidades existentes em uma configuração móvel é a sua imprevisibilidade quanto às suas conexões, assim, desconexões são usualmente freqüentes em ambientes móveis. Esta dissertação apresenta uma pesquisa sobre o tratamento das desconexões de dispositivos móveis utilizados pelos usuários para submissão e monitoração de aplicações em ambientes de grids computacionais. O conceito de workflow foi empregado para a submissão e monitoração de aplicações com várias tarefas para solução de um único problema. A abordagem proposta é constituída por um mecanismo de tratamento de falhas que possui três componentes: o observador, o analisador e o adaptador. Nos casos de desconexão, o mecanismo desenvolvido adapta o fluxo de execução das aplicações considerando a natureza da aplicação e as configurações prévias do usuário. Com a execução dos testes experimentais observou-se que o mecanismo proposto atua na verificação do status de conexão e, quando necessário, procede ao ajuste na execução da aplicação. Em adição, a abordagem possibilita o reinício de aplicações não finalizadas, sem perder o processamento já realizado. Neste contexto, o mecanismo garante a consistência das aplicações de maneira transparente para o usuário, bem como evita o desperdício dos recursos do ambiente grid. Desta forma, a abordagem atingiu com sucesso o objetivo de uma melhor utilização de um ambiente de grid computacional, através de um dispositivo móvel, considerando-se suas eventuais desconexões

An Architecture for Managing Data Privacy in Healthcare with Blockchain

With the fast development of blockchain technology in the latest years, its application in scenarios that require privacy, such as health area, have become encouraged and widely discussed. This paper presents an architecture to ensure the privacy of health-related data, which are stored and shared within a blockchain network in a decentralized manner, through the use of encryption with the RSA, ECC, and AES algorithms. Evaluation tests were performed to verify the impact of cryptography on the proposed architecture in terms of computational effort, memory usage, and execution time. The results demonstrate an impact mainly on the execution time and on the increase in the computational effort for sending data to the blockchain, which is justifiable considering the privacy and security provided with the architecture and encryption.N/

Impact: an Unreliable Failure Detector Based on Processes' Relevance and the Confidence Degree in the System

This technical report presents a new unreliable failure detector, called the Impact failure detector (FD) that, contrarily to the majority of traditional FDs, outputs a trust level value which expresses the degree of confidence in the system. An impact factor is assigned to each node and the trust level is equal to the sum of the impact factors of the nodes not suspected of failure. Moreover, a threshold parameter defines a lower bound value for the trust level, over which the confidence in the system is ensured. In particular, we defined a flexibility property that denotes the capacity of the Impact FD to tolerate a certain margin of failures or false suspicions, i.e., its capacity of considering different sets of responses that lead the system to trusted states. The Impact FD is suitable for systems that present node redundancy, heterogeneity of nodes, clustering feature, and allow a margin of failures which does not degrade the confidence in the system. The technical report also includes a timer-based distributed algorithm which implements a Impact FD, as well as its proof of correctness, for systems whose links are lossy asynchronous or for those whose all (or some) links are eventually timely. Performance evaluation results based on real PlanetLab traces confirm the degree of flexible applicability of our failure detector and, due to the accepted margin of failure, the both failures and false suspicions are more tolerated when compared to traditional unreliable failure detectors. We also show the equivalence of some classes of Impact FD in regard with Sigma and Omega classes, which are fundamental classes to circumvent the impossibility of consensus in asynchronous message-passing distributed systems

Protagonismo dos estudantes que desenvolvem atividades junto a um núcleo de tecnologia

Os avanços tecnológicos têm contribuído em diversas áreas do conhecimento, porém quando olhamos para a educação ainda vemos presente, muitas vezes, a metodologia de instrucionismo engessada e antiquada. Neste sentido, este trabalho busca alternativas construtivistas aliadas à tecnologia para o desenvolvimento do protagonismo dos estudantes. Por meio da aplicação de oficinas sobre tópicos em tecnologia em um laboratório maker com participantes do ensino médio, buscou-se implementar atividades que contribuam com o desenvolvimento cognitivo dos aprendizes. Com a realização de encontros, planejados em diferentes momentos, foi possível conduzir uma discussão fazendo a relação entre as percepções dos estudantes, as teorias construtivistas e os conceitos da cultura maker com vistas a adoção do papel de protagonista. Os resultados obtidos evidenciam que diferentes abordagens para o ensino de tecnologia contribuem para o desenvolvimento do estudante em seu processo de aprendizagem

Impact FD: An Unreliable Failure Detector Based on Process Relevance and Confidence in the System

International audienceThis paper presents a new unreliable failure detector, called the Impact failure detector (FD) that, contrarily to the majority of traditional FDs, outputs a trust level value which expresses the degree of confidence in the system. An impact factor is assigned to each process and the trust level is equal to the sum of the impact factors of the processes not suspected of failure. Moreover, a threshold parameter defines a lower bound value for the trust level, over which the confidence in the system is ensured. In particular, we defined a f l exi bi l i t y property that denotes the capacity of the Impact FD to tolerate a certain margin of failures or false suspicions, i.e., its capacity of considering different sets of responses that lead the system to trusted states. The Impact FD is suitable for systems that present node redundancy, heterogeneity of nodes, clustering feature, and allow a margin of failures which does not degrade the confidence in the system. The paper also includes a timer-based distributed algorithm which implements an Impact FD, as well as its proof of correctness, for systems whose links are lossy asynchronous or for those whose all (or some) links are eventually timely. Performance evaluation results, based on PlanetLab [1] traces, confirm the degree of flexible applicability of our failure detector and that, due to the accepted margin of failure, both failures and false suspicions are more tolerated when compared to traditional unreliable failure detectors

MultiS: A Context-Server for Pervasive Computing

AbstractContext-aware applications are capable of recognizing environmental changes and adapting their behavior to the new context. This process can be divided into three stages: monitoring, context recognition and adaptation. On the monitoring layer, raw information about the environment is collected from sensors. The context recognition layer processes the data acquired from the context and transforms it into information which can be useful for the adaptation process. With this information, the adaptation system can determine what behavior is correct for the application in each different context. This paper proposes a context server called MultiS, which has the goal of solving the problems arising from the context recognition layer, and which includes the following advantages: a) the production of new context data based on the information of several sensors and an ability to react to changes in the environment; b) definition of a composed language for the context data called CD-XML; c) support for mobility

Analysis of a hybrid neural network as underlying mechanism for a situation prediction engine

This paper presents the results regarding a technique that can be used as an underlying mechanism for situation prediction. We analysed a hybrid neural network called Multi-output Adaptive Neural Fuzzy Inference System (MANFIS) and compared its predictive ability with a Multi-Layer Perceptron (MLP). The results demonstrate that, depending on the application, the use of neural networks can be considered to be a good approach for situation prediction, when combined with other techniques.Key words: situation, context, prediction, neural networks, MANFIS

Implementing a flexible failure detector that expresses the confidence in the system

International audienceTraditional unreliable failure detectors are per process oracles that provide a list of nodes suspected of having failed. Previously, we introduced the Impact failure detector that outputs a trust level value which is the degree of confidence in the system. An impact factor is assigned to each node and the trust level is equal to the sum of the impact factors of the nodes not suspected to have failed. An input threshold parameter definesan impact factor limit value, over which the confidence degree on the system is ensured. The impact factor indicates the relative importance of the process in the set S, while the threshold offers a degree of flexibility for failures and false suspicions.We propose in this article two different algorithms, based on query-response message rounds, that implement the Impact FD whose conceptions were tailored to satisfy the Impact FD’s flexibility. The first one exploits the time-free message pattern approach while the second one considers a set of bounded timely responses. We also introduced the concept that a process can be PS−accessible (or ♦PS−accessible) which guarantees that the system S will always (or eventually always) be trusted to this process as well as two properties, P R(IT ) and PR(♦IT ), that characterize the minimum necessary stability condition of S that ensures confidence (or eventual confidence) on it. In both implementations, if the process that monitors S is P S−accessible or ♦PS−accessible, at every query round, it only waits (or eventually only waits) for a set of responsethat satisfy the threshold. A crucial facet of this set of processes is that it is not fixed, i.e., the set of processes can change at each round, which is in accordance with the flexibility capacity of the Impact FD

Uma Proposta de Mecanismo de Autoadaptação para Sistemas de Sensoriamento Urbano

Este artigo apresenta um estudo da Computação Autonômica (CA) aplicado na literatura de sensoriamento urbano. A análise revela que o ponto de vista da CA ainda não foi totalmente explorado por tais trabalhos. Nesse sentido, um mecanismo de autoadapação com base no modelo de MAPE-K é proposto com o objetivo de proporcionar um componente genérico capaz de tratar os pontos identificados. Como avaliação preliminar, o mecanismo proposto foi incorporado na implementação da arquitetura UrboSenti para dispositivos móveis e desktop visando discutir as observações encontradas.Palavras-chave: Computação Autônoma, Sensoriamento Urbano, Sistemas Autoadaptativos, Computação Móvel