Categorization of Cloud Workload Types with Clustering
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.
Piotr Orzechowski, Jerzy Proficz, Henryk Krawczyk, Julian Szymański. (2017). Categorization of Cloud Workload Types with Clustering. Proceedings Of The International Conference On Signal, Networks, Computing, And Systems. - Vol. 1, 395, 303-313. https://doi.org/10.1007/978-81-322-3592-7_31
wyświetlono 38 razy