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Abstract
The paper presents an approach to automatic discovery of workloads types. We perform functional characteristics of the workloads executed in our cloud environment, that have been used to create model of the computations. To categorize the resources utilization we used K-means algorithm, that allow us automatically select six types of computations. We perform analysis of the discovered types against to typical computational benchmarks, finding the strong correlation between functional classes and the resource utilization.
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- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Title of issue:
- Proceedings of 2016 6th International Workshop on Computer Science and Engineering (WCSE 2016) strony 453 - 457
- Language:
- English
- Publication year:
- 2016
- Bibliographic description:
- Orzechowski P., Proficz J., Krawczyk H., Szymański J.: Automatic Discovery of IaaS Cloud Workload Types// Proceedings of 2016 6th International Workshop on Computer Science and Engineering (WCSE 2016)/ Rowland Heights: , 2016, s.453-457
- Verified by:
- Gdańsk University of Technology
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