Leveraging History to Predict Infrequent Abnormal Transfers in Distributed Workflows †

Scientific computing heavily relies on data shared by the community, especially in distributed data-intensive applications. This research focuses on predicting slow connections that create bottlenecks in distributed workflows. In this study, we analyze network traffic logs collected between January...

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Detalles Bibliográficos
Autores principales: Shao, Robin, Sim, Alex, Wu, Kesheng, Kim, Jinoh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10300713/
https://www.ncbi.nlm.nih.gov/pubmed/37420657
http://dx.doi.org/10.3390/s23125485

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10300713/
https://www.ncbi.nlm.nih.gov/pubmed/37420657
http://dx.doi.org/10.3390/s23125485

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