Manage Storage Resources Efficiently Using Predictive Analytics
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-59635-4_15
Reference17 articles.
1. Baldan, F.J., Ramirez-Gallego, S., Bergmeir, C., Herrera, F.: A forecasting methodology for workload forecasting in cloud systems. IEEE Trans. Cloud Comput. 6(4), 929–941 (2018). https://doi.org/10.1109/TCC.2016.2586064
2. Cuong, S.V., Davydenko, A., Shcherbakov, M.: Data schemas for forecasting (with examples in R). In: 2018 International Conference on System Modeling & Advancement in Research Trends. IEEE (2018). https://doi.org/10.1109/sysmart.2018.8746985
3. Kawano, H.: Hierarchical storage systems and file formats for web archiving. In: 2011 21st International Conference on Systems Engineering. IEEE Press (2011). https://doi.org/10.1109/icseng.2011.46
4. Subramaniyam, M., et al.: A data-driven algorithm to predict throughput bottlenecks in a production system based on active periods of the machines. Comput. Ind. Eng. 125, 533–544 (2018)
5. Springer Proceedings in Business and Economics;J Calvimontes,2020
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