Development of a method for selecting the approximatimg functions for the observable processes of cloud infrastructure
This paper considers the techniques for improving the effectiveness of monitoring the cloud infrastructure processes implying the reduction of a computational burden while maintaining the required level of measurement accuracy. A technique for organizing the monitoring of cloud infrastructure proces...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
PC Technology Center
2020-04-01
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| Series: | Eastern-European Journal of Enterprise Technologies |
| Subjects: | |
| Online Access: | http://journals.uran.ua/eejet/article/view/200372 |
| Summary: | This paper considers the techniques for improving the effectiveness of monitoring the cloud infrastructure processes implying the reduction of a computational burden while maintaining the required level of measurement accuracy. A technique for organizing the monitoring of cloud infrastructure processes, based on the approximation of accumulated measurements, has been further developed in this study. The necessary and sufficient set of approximating functions has been built, corresponding to the key properties of the observable processes. A method for selecting the approximating functions for the observable cloud infrastructure processes has been constructed. The method implies the assessment of properties of an observable process and the selection of its approximating function.
The practical value of this research relates to the ability to reduce the computational burden by reducing the number of planned measurements at an acceptable level of the decrease in their accuracy. The originality of the approach is the use of the a priori data about the observable processes aimed to obtain more accurate estimates of their properties. The practical implementation of the proposed method shows a 20–40 % decrease in the number of planned measurements at the level of monitoring accuracy not lower than 95 %. The proposed method makes it possible to reduce the load on cloud infrastructure components, to decrease the use of processor time, as well as the disk and random-access memories of physical and virtual nodes. The results of the study can be used for the software implementation of the system of cloud infrastructure monitoring |
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| ISSN: | 1729-3774 1729-4061 |