01. Universidade Federal Rural de Pernambuco - UFRPE (Sede)
URI permanente desta comunidadehttps://arandu.ufrpe.br/handle/123456789/1
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8 resultados
Resultados da Pesquisa
Item CIMut: ferramenta de injeção de falhas em ambientes de nuvens por mutação(2025-02-13) Duarte, Guilherme Silva; Sousa, Erica Teixeira Gomes de; http://lattes.cnpq.br/9899077867723655; http://lattes.cnpq.br/6937961051628049A injeção de falhas de software é uma técnica valiosa para avaliar a resiliência de sistemas de software complexos. Ao introduzir falhas em componentes específicos, os pesquisadores podem observar como essas falhas se propagam e impactam o comportamento geral do sistema. Este artigo apresenta a ferramenta CIMut, desenvolvida para injeção de falhas por meio da mutação do código-fonte. A mutação do código-fonte possibilita a introdução de falhas para análise de sistemas. Um estudo experimental abrangente realizado no OpenStack, uma plataforma de computação em nuvem de código aberto, demonstra a eficácia da ferramenta. Foram realizados mais de 62 experimentos no OpenStack, cada um injetando falhas em diferentes componentes do sistema. Os resultados do estudo foram promissores. Uma parcela significativa (até 96,7%) das falhas injetadas resultou em bugs, classificados como erros explícitos (travamentos, exceções) ou bugs com impacto funcional (comportamento incorreto, perda de dados). Esses resultados demonstram que a ferramenta CIMut é capaz de gerar falhas representativas que podem ser utilizadas para avaliar a resiliência de sistemas de software complexos como o OpenStack.Item Comparação de VPN e ZTNA: uma análise de segurança e desempenho em ambientes corporativo(2024-09-30) Chagas, Marcelino Francisco Gomes das; Medeiros, Robson Wagner Albuquerque de; http://lattes.cnpq.br/3169193612606500Constant technological advances and the rapid expansion of infrastructures in public cloud providers have created significant challenges for companies, especially with regard to information security. Traditional security measures, such as Virtual Private Networks (VPNs), which create a secure tunnel for data transmission between the user and the corporate network, are not always adequate to protect data in cloud environments, resulting in a growing need to re-evaluate protection strategies. The COVID-19 pandemic has further intensified this demand, as organizations have been forced to adopt remote working practices on a large scale. In this scenario, trust in the final data has become a critical concern, especially given the limitations of traditional VPN solutions. In response to these challenges, Zero Trust Architecture (ZTA) and Zero Trust Network Access (ZTNA) have emerged as promising approaches. ZTNA is a technology based on the principles of ZTA that redefines network access control by eliminating implicit trust in any user or device, regardless of their location, and requiring continuous verification for every access attempt. This approach offers more granular security at the network and access control level, and is adaptable in on-premise and cloud environments, protecting data in distributed and constantly evolving corporate environments. The aim of this work is to carry out a comparative analysis of VPN and ZTNA network technologies, with an emphasis on evaluating security and performance. The security features offered by each technology will be examined, including authentication, access control and encryption, as well as the impact of these technologies on network performance in terms of latency, bandwidth and response time. Through this analysis, we aim to identify the advantages and disadvantages of each technological approach, offering valuable insights for IT professionals and organizations in selecting and implementing the solution best suited to their security and performance needs in modern corporate environments.Item Desenvolvimento de uma infraestrutura em nuvem para monitoramento de ninhos de tartarugas marinhas(2024-03-08) Silva, Wanderson Moura da; Medeiros, Victor Wanderley Costa de; http://lattes.cnpq.br/7159595141911505This Course Completion Work proposes a monitoring system for sea turtle nesting, using the ThingsBoard platform to create a monitoring dashboard. The study seeks to integrate Internet of Things (IoT) technologies and community involvement strategies to improve the conservation of these species, whose existence has long been threatened by various predatory factors. The application on the ThingsBoard platform makes it possible to obtain essential data in real time, such as movement and temperature from devices installed inside the nest. The implemented dashboard will provide a clear visual representation of the status of each monitored nest, automatically generating an alert when critical events occur, such as an excessive increase in temperature or movements that cause the incubated eggs to hatch. The dashboard, in addition to providing crucial information for researchers and environmentalists, will be accessible to the local community through an exclusive mobile application. The project review encompasses ongoing improvement strategies, emphasizing collaboration with local experts and active community participation to optimize the effectiveness of the monitoring application. The central role of the dashboard developed on the ThingsBoard platform is to receive and present data from devices installed in turtle nests, to monitor temperature and movement. This system facilitates understanding and analysis of data, providing insights into the possibility of egg hatching, and contributing to the effective conservation of sea turtles.Item Uma metodologia para a avaliação de desempenho e custos do treinamento de redes neurais em ambientes de nuvem(2024-03-07) Moura Filho, Cláudio Márcio de Araújo; Sousa, Érica Teixeira Gomes de; http://lattes.cnpq.br/9899077867723655; http://lattes.cnpq.br/8143173691280119Deep neural networks are solutions to problems involving pattern recognition and several works try to find ways to optimize the performance of these networks. This optimization requires suitable hardware to be implemented, hardware that can be very expensive for small and medium-sized organizations. The objective of this work is to propose a methodology to evaluate the performance and cost of training neural networks, considering the factors that most impact training time and evaluate the total financial cost of the environment for this task. In this sense, it was observed that factors such as the size of the input image and the network architecture have a great impact on the training time metric and consequently on the total cost.Item Uma revisão sistemática sobre avaliação do consumo de energia em nuvem das coisas(2021-12-10) Ferreira, Emerson Severino de Oliveira Ramos; Sousa, Erica Teixeira Gomes de; http://lattes.cnpq.br/9899077867723655; http://lattes.cnpq.br/9000455288391839IoT devices are used in many types of vertical industries and consumer markets. In 2020 there were around 8 billion devices connected around the world, and the forecast for 2030 is to have more than 25 billion devices connected. Furthermore, the world market for IoT devices in the government area alone will transact around $21 billion in 2022, where more than 50% of that amount will be for external surveillance equipment. Which represents a 36% increase in comparison with 2020. Nowadays, research is heading towards the integration of Cloud Computing and the Internet of Things (IoT), thus creating the concept of Cloud of Things (CoT). CoT aims to offer computational resources in a pervasive and ubiquitous way, in which IoT characteristics are available as services through Cloud Computing. In CoT, Cloud acts as a middleware that makes the interaction between objects (Things) and users/applications in a transparent way, eliminating the complexity which facilitates the development of applications that interact with smart objects, which facilitate their utilization in areas as Healthcare, Smart Cities, Smart Home, Video Surveillance, Smart Mobility, Smart Energy and others.In CoT environments, a large amount of communication and data transmission affected by IoT devices degrade the energy efficiency of these environments, affecting the quality of services. In this way, this work describes a systematic review the strategies for evaluating the energy consumption in Cloud of Things. This systematic review aims to bring together published studies related to energy consumption assessment in IoT and Cloud of Things, for an analysis of the methodologies employed in these works and proposition of future work, about cloud of things energy consumption assessment.Item Uma análise do impacto das linguagens de programação nos custos de execução no AWS Lambda em cenários de cold start e warm start(2023-04-24) Andrade Júnior, Edilson Alves de; Medeiros, Robson Wagner Albuquerque de; http://lattes.cnpq.br/3169193612606500; http://lattes.cnpq.br/5131828050788518Public cloud computing solutions have gained visibility on the market for offering great advantages over on-premises systems. However, cloud-based management workflows also brings concerns. As well as problems related to information security and lack of skilled professionals, cost management is one of the main challenges faced by users and organizations that migrate or already have their operations on cloud. Cloud providers define variables that directly affect cost behaviors, in addition, factors such as key characteristics of programming languages can also contribute to change those behaviors. This work aimed to understand how programming languages behave in cloud services such as AWS Lambda, so that cost management is carried out more assertively and efficiently, directly contributing to the reduction of costs and financial waste when using this kind of service. The results showed that the characteristics of programming languages significantly interfere in the financial costs of execution, elucidating that the choice of a certain programming language should be considered when cost is a requirement to be met when using AWS Lambda.Item Obtenção de modelos QSAR na plataforma livre de computação em nuvem OCHEM e uma aplicação para atividade acaricida de monoterpenos(2022-06-08) Silva, Esterfania Laís da; Batista, Hélcio José; http://lattes.cnpq.br/1234630357325796; http://lattes.cnpq.br/0889940460113959The present work focuses in using the resources of the free access cloud computing web platform OCHEM - English Online Chemical Modeling Environment, designed for data storage, development of models and publication of chemical information. As an example of application on the platform, we sought to obtain QSAR models - Quantita-tive Structure-Activity Relation for insecticidal activity on the species of Spider Mite (Tetranychus Urticae), a common pest in family farming in the Northeast region of Bra-zil, from a series of compounds of the monoterpene class: α-pinene, p-cymene, β-pinene, menthol, α-terpineol, geraniol, R-limonene, 1-8-cineole, R-linalool, terpenyl ac-etate, and terpinolene and 4- (S) ter-pineol. To this end, we carried out a literature review on the monoterpenes usage in agriculture pest control, as well as a review of the Quantitative Structure-Activity Relation-ship method, QSAR. For the application of the OCHEM platform to obtain QSAR models for the series of monoterpenes, we per-formed the molecular modeling of the series compounds by methods of Quantum Chemistry, generating the molecular structures in order to feed the OCHEM platform, to calculate the molecular descriptors and obtain of QSAR models. We explored differ-ent sets of descriptors as well as different types of machine learning methods, such as Multiple Linear Regression (MLR), Partial Least Squares (PLS) and Neural Networks (NN - Neural Networks). The models so obtained for the series under study, however, did not have sufficient statistical quality, probably due, firstly, to the small number of compounds in the training set with available experimental data and, also, to a likely strong degree of non-linearity present in the relationship between the chosen de-scriptors and the activity.Item O consumo de jogos digitais no Brasil em 2021 e o uso de cloud gaming como uma resposta à pirataria(2021-12-16) França, Eric Ferreira de; Araújo, Chiara Natércia França; http://lattes.cnpq.br/7273384016233113The main goal of this academic work was to analyze the possibility of using cloud gaming as an answer to piracy and as cheaper way to get into the digital games market. It is noteworthy that this analysis is limited to a group of Brazilian players who were divided between hardcore and casual gamers and to the year 2021. For that, it was necessary to analyze secondary data collected from Pesquisa Game Brasil 2021; information in academic works by authors such as Victor Barros and Ana Paula Martins; and, journalistic articles published by the specialized media, in order to know the gamers’ profile. Primary data were collected through a quantitative survey, conducting a brief online questionnaire in a group of 121 Brazilians using the tools available on Google Forms. Such analyzes served as a basis to obtain a hypothetical profile of consumer behavior. Regarding cloud gaming, 98,9% of players from both groups agreed that this is a more affordable way to consume electronic games, and also considered the possibility that consumers will spend less money on games thanks to this technology, however, 54,9% of players do not consider it as the ultimate solution against piracy, but it may have an impact on the consumption of illegal copies in the future.