Toward Pattern-based Model Selection for Cloud Resource Forecasting

Author:

Christofidi Georgia1ORCID,Papaioannou Konstantinos1ORCID,Doudali Thaleia Dimitra1ORCID

Affiliation:

1. IMDEA Software Institute, Madrid, Spain

Funder

MCIN/AEI/10.13039/501100011033 and the European Union «NextGenerationEU»/PRTR

Publisher

ACM

Reference35 articles.

1. 2018. Alibaba Open Trace. https://github.com/alibaba/clusterdata 2018. Alibaba Open Trace. https://github.com/alibaba/clusterdata

2. 2019. Azure Public Dataset. https://github.com/Azure/AzurePublicDataset 2019. Azure Public Dataset. https://github.com/Azure/AzurePublicDataset

3. David Arthur and Sergei Vassilvitskii . 2007 . K-Means++: The Advantages of Careful Seeding . In Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms ( New Orleans, Louisiana) (SODA '07). Society for Industrial and Applied Mathematics, USA, 1027--1035. David Arthur and Sergei Vassilvitskii. 2007. K-Means++: The Advantages of Careful Seeding. In Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms (New Orleans, Louisiana) (SODA '07). Society for Industrial and Applied Mathematics, USA, 1027--1035.

4. Luiz Andr Barroso , Jimmy Clidaras , and Urs Hlzle . 2013. The Data-center as a Computer: An Introduction to the Design of Warehouse-Scale Machines ( 2 nd ed.). Morgan & Claypool Publishers . Luiz Andr Barroso, Jimmy Clidaras, and Urs Hlzle. 2013. The Data-center as a Computer: An Introduction to the Design of Warehouse-Scale Machines (2nd ed.). Morgan & Claypool Publishers.

5. Take it to the limit

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1. Is Machine Learning Necessary for Cloud Resource Usage Forecasting?;Proceedings of the 2023 ACM Symposium on Cloud Computing;2023-10-30

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