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...

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Main Authors: Oleksii Grytsenko, Vladimir Sayenko
Format: Article
Language:English
Published: PC Technology Center 2020-04-01
Series:Eastern-European Journal of Enterprise Technologies
Subjects:
Online Access:http://journals.uran.ua/eejet/article/view/200372
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spelling doaj-822c2e0c6dde4198aed819b2182d5a572020-11-25T02:09:51ZengPC Technology CenterEastern-European Journal of Enterprise Technologies1729-37741729-40612020-04-0122 (104)172410.15587/1729-4061.2020.200372200372Development of a method for selecting the approximatimg functions for the observable processes of cloud infrastructureOleksii Grytsenko0Vladimir Sayenko1Kharkiv National University of Radio Electronics Nauky ave., 14, Kharkiv, Ukraine, 61166Kharkiv National University of Radio Electronics Nauky ave., 14, Kharkiv, Ukraine, 61166This 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 monitoringhttp://journals.uran.ua/eejet/article/view/200372cloud infrastructure monitoringcomputer networkfunction approximationcomputational burden
collection DOAJ
language English
format Article
sources DOAJ
author Oleksii Grytsenko
Vladimir Sayenko
spellingShingle Oleksii Grytsenko
Vladimir Sayenko
Development of a method for selecting the approximatimg functions for the observable processes of cloud infrastructure
Eastern-European Journal of Enterprise Technologies
cloud infrastructure monitoring
computer network
function approximation
computational burden
author_facet Oleksii Grytsenko
Vladimir Sayenko
author_sort Oleksii Grytsenko
title Development of a method for selecting the approximatimg functions for the observable processes of cloud infrastructure
title_short Development of a method for selecting the approximatimg functions for the observable processes of cloud infrastructure
title_full Development of a method for selecting the approximatimg functions for the observable processes of cloud infrastructure
title_fullStr Development of a method for selecting the approximatimg functions for the observable processes of cloud infrastructure
title_full_unstemmed Development of a method for selecting the approximatimg functions for the observable processes of cloud infrastructure
title_sort development of a method for selecting the approximatimg functions for the observable processes of cloud infrastructure
publisher PC Technology Center
series Eastern-European Journal of Enterprise Technologies
issn 1729-3774
1729-4061
publishDate 2020-04-01
description 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
topic cloud infrastructure monitoring
computer network
function approximation
computational burden
url http://journals.uran.ua/eejet/article/view/200372
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AT vladimirsayenko developmentofamethodforselectingtheapproximatimgfunctionsfortheobservableprocessesofcloudinfrastructure
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