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,...

The paper presents a method of hardware load prediction using workload models based on application categories and high-level characteristics. Application of the method to the problem of optimization of virtual machine scheduling in a heterogeneous Infrastructure as a Service (IaaS) computing cloud is described.

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...

Głębokie zmiany, jakie zachodzą w informatyce, polegające na przejściu od fundamentalnych aplikacji i ich wsparcia infrastrukturą informatyczną do traktowania oprogramowania jako usługi SaaS (ang.Software-as-a-Service) oraz infrastruktury informatycznej jako usługi IaaS (ang. Infrastructure-as-a-Service), wymuszają gruntowne zmiany również w procesach kształcenia.