Previsão de falhas em ambientes de nuvem: uma revisão sistemática de literatura
DOI:
https://doi.org/10.18265/2447-9187a2022id8011Palavras-chave:
aprendizagem de máquina, computação em nuvem, previsão de falhas, revisão sistemáticaResumo
Atualmente, os serviços de computação em nuvem são fundamentais para a economia moderna. Diversos setores têm reorientado seus serviços para a nuvem. No entanto, a complexidade e natureza distribuída desses sistemas contribuem para a ocorrência de diversos tipos de falhas que, quando não tratadas, podem resultar em danos catastróficos. Para mitigar os efeitos das falhas, diversos métodos de previsão de falhas foram propostos. Como esses métodos mudam com o passar do tempo, esse trabalho tem como objetivo apresentar uma revisão sistemática da literatura a respeito das técnicas e métodos utilizados na previsão de falhas em nuvem. Nesse sentido, 40 artigos de quatro bases de dados cientificamente reconhecidas foram analisados. Ficou evidenciada a predominância de técnicas de aprendizagem de máquina baseadas em árvore de decisão, assim como a escassez de conjuntos de dados do mundo real para o avanço das pesquisas de previsão de falhas em nuvem. Esforços de pesquisa futuros podem avaliar métodos para agregar as amostras de dados de trabalhos e tarefas no conjunto de dados, bem como técnicas para balanceamento de classes em modelos de previsão de falhas em nuvem. Essa revisão sistemática da literatura apresenta o estado atual das pesquisas relacionadas à previsão de falhas nos sistemas em nuvem. As observações e tendências identificadas neste trabalho podem ser úteis para futuros pesquisadores.
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