Categorization of Cloud Workload Types with Clustering - Publikacja - MOST Wiedzy

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Categorization of Cloud Workload Types with Clustering

Abstrakt

The paper presents a new classification schema of IaaS cloud workloads types, based on the functional characteristics. We show the results of an experiment of automatic categorization performed with different benchmarks that represent particular workload types. Monitoring of resource utilization allowed us to construct workload models that can be processed with machine learning algorithms. The direct connection between the functional classes and the resource utilization was shown, using unsupervised categorization approach based on moving average for finding a class number, and k-means algorithm for clustering.

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Piotr Orzechowski, Jerzy Proficz, Henryk Krawczyk, Julian Szymański. (2017). Categorization of Cloud Workload Types with Clustering, 395, 303-313. https://doi.org/10.1007/978-81-322-3592-7_31

Informacje szczegółowe

Kategoria:
Inna publikacyjna praca zbiorowa (w tym materiały konferencyjne)
Typ:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Tytuł wydania:
Proceedings of the International Conference on Signal, Networks, Computing, and Systems. - Vol. 1 strony 303 - 313
ISSN:
1876-1100
Rok wydania:
2017
Opis bibliograficzny:
Orzechowski P., Proficz J., Krawczyk H., Szymański J.: Categorization of Cloud Workload Types with Clustering// Proceedings of the International Conference on Signal, Networks, Computing, and Systems. - Vol. 1/ : Springer India, 2017, s.303-313

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