dc.contributorMarcondes, César Augusto Cavalheiro
dc.contributorhttp://lattes.cnpq.br/4431183539132719
dc.contributorhttp://lattes.cnpq.br/1718499653531495
dc.creatorAlves, Renato dos Santos
dc.date.accessioned2016-11-08T18:44:39Z
dc.date.available2016-11-08T18:44:39Z
dc.date.created2016-11-08T18:44:39Z
dc.date.issued2016-08-10
dc.identifierALVES, Renato dos Santos. Rede Bayesiana empregada no gerenciamento da saúde dos sistemas na computação em nuvem. 2016. Dissertação (Mestrado em Ciência da Computação) – Universidade Federal de São Carlos, São Carlos, 2016. Disponível em: https://repositorio.ufscar.br/handle/ufscar/8283.
dc.identifierhttps://repositorio.ufscar.br/handle/ufscar/8283
dc.description.abstractCloud computing is a convenient computing model, because it allows the ubiquity with on-demand access to a set of configurable and shared features, that can be rapidly provisioned and made available with minimal effort or interaction with the service provider. IaaS is a different way to deliver cloud computing, where infrastructure servers, networking systems, storage, and all the necessary environment for the operating system to run the application are hired as services. Meanwhile, traditional companies still have doubts in relation to the transferring of their data outside of the limits of the corporation. The health of cloud computing systems is fundamental to the business, given the complexity of the systems it is difficult to ensure that all services and resources will work properly. In order to ensure a more appropriate management of the systems and services in the cloud, an architecture is proposed. The architecture has been modularized through specializing monitoring functions, data mining, and inference with Bayesian network. In this architecture are essential records of event monitoring systems and computing resources because the recorded data is mined to identify fault patterns a given system after the result of one or more events in the environment. For mining the monitoring data we proposed two algorithms, one for performing preprocessing of data and another to perform data transformation. As a data mining product obtained, data sets that were the input to create a Bayesian network. Through structural and parametric learning algorithms Bayesinas networks for each systems and services offered by cloud computing were created. The Bayesian network is intended to assist in decision making with prevention, prediction, error correction in systems and services, allowing to manage the health and performance of the most appropriate way systems. To check the compliance of the fault diagnosis of this architecture, we validate accuracy of inference of Bayesian network with cross-validation method using data sets generated by monitoring systems and services.
dc.languagepor
dc.publisherUniversidade Federal de São Carlos
dc.publisherUFSCar
dc.publisherPrograma de Pós-Graduação em Ciência da Computação - PPGCC
dc.publisherCâmpus São Carlos
dc.rightsAcesso aberto
dc.subjectIaaS
dc.subjectMineração de dados
dc.subjectComputação em nuvem
dc.subjectRede bayesiana
dc.subjectSaúde de sistemas
dc.subjectCloud computing
dc.subjectData mining
dc.subjectStructural learning
dc.subjectBayesian network
dc.subjectHealth systems
dc.titleRede Bayesiana empregada no gerenciamento da saúde dos sistemas na computação em nuvem
dc.typeTesis


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