Algorithm for Load Balancing of a Data Processing Center Based on a Nonlinear Forecast Model

The purpose of the article is to increase the efficiency of the cloud data center load distribution and balancing system by developing and applying a mechanism for predicting network traffic conditions characterized by fractal self-similarity. When developing the predictive model, methods of nonline...

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Prif Awduron:	Mochalov, V. P., Мочалов, В. П., Bratchenko, N. Y., Братченко, Н. Ю., Gosteva, D. V., Гостева, Д. В.
Fformat:	Статья
Iaith:	English
Cyhoeddwyd:	Institute of Electrical and Electronics Engineers Inc. 2024
Pynciau:	Fractal network traffic Singular spectral analysis Load balancing Prediction Self-similarity
Mynediad Ar-lein:	https://dspace.ncfu.ru/handle/123456789/29324
Tagiau:	Ychwanegu Tag Dim Tagiau, Byddwch y cyntaf i dagio'r cofnod hwn!

id	ir-123456789-29324
record_format	dspace
spelling	ir-123456789-293242024-12-06T08:52:24Z Algorithm for Load Balancing of a Data Processing Center Based on a Nonlinear Forecast Model Mochalov, V. P. Мочалов, В. П. Bratchenko, N. Y. Братченко, Н. Ю. Gosteva, D. V. Гостева, Д. В. Fractal network traffic Singular spectral analysis Load balancing Prediction Self-similarity The purpose of the article is to increase the efficiency of the cloud data center load distribution and balancing system by developing and applying a mechanism for predicting network traffic conditions characterized by fractal self-similarity. When developing the predictive model, methods of nonlinear dynamics were used, taking into account the statistical self-similarity of the load and providing a solution to the problem of predicting the moments of its expected bursts. The randomness of network traffic was checked by calculating the spectrum of Lyapunov exponents. The mathematical model and the dynamic algorithm of the predictive model of the state of a nonlinear system are presented in the form of a system of discrete mappings of previous and subsequent values of a time series and a regression approximating polynomial connecting them. The presented algorithm differs from the existing ones by taking into account the features of fractal self-similarity of the input load, which negatively affects quality indicators, using a predictive model developed on the basis of nonlinear dynamics methods, as well as the possibility of choosing rational balancing parameters according to the criterion of uniform loading of server resources. The article shows that the dynamic load balancing algorithm, based on nonlinear approaches and predictive models, allows solving load distribution problems between servers of data center clusters more efficiently than traditional methods. The conclusion about the effectiveness of the developed algorithm is substantiated. 2024-12-06T08:51:10Z 2024-12-06T08:51:10Z 2024 Статья Mochalov, V.P., Bratchenko, N.Yu., Gosteva, D.V. Algorithm for Load Balancing of a Data Processing Center Based on a Nonlinear Forecast Model // RusAutoCon - Proceedings of the International Russian Automation Conference. - 2024. - pp. 350-355. - DOI: 10.1109/RusAutoCon61949.2024.10694233 https://dspace.ncfu.ru/handle/123456789/29324 en RusAutoCon - Proceedings of the International Russian Automation Conference application/pdf Institute of Electrical and Electronics Engineers Inc.
institution	СКФУ
collection	Репозиторий
language	English
topic	Fractal network traffic Singular spectral analysis Load balancing Prediction Self-similarity
spellingShingle	Fractal network traffic Singular spectral analysis Load balancing Prediction Self-similarity Mochalov, V. P. Мочалов, В. П. Bratchenko, N. Y. Братченко, Н. Ю. Gosteva, D. V. Гостева, Д. В. Algorithm for Load Balancing of a Data Processing Center Based on a Nonlinear Forecast Model
description	The purpose of the article is to increase the efficiency of the cloud data center load distribution and balancing system by developing and applying a mechanism for predicting network traffic conditions characterized by fractal self-similarity. When developing the predictive model, methods of nonlinear dynamics were used, taking into account the statistical self-similarity of the load and providing a solution to the problem of predicting the moments of its expected bursts. The randomness of network traffic was checked by calculating the spectrum of Lyapunov exponents. The mathematical model and the dynamic algorithm of the predictive model of the state of a nonlinear system are presented in the form of a system of discrete mappings of previous and subsequent values of a time series and a regression approximating polynomial connecting them. The presented algorithm differs from the existing ones by taking into account the features of fractal self-similarity of the input load, which negatively affects quality indicators, using a predictive model developed on the basis of nonlinear dynamics methods, as well as the possibility of choosing rational balancing parameters according to the criterion of uniform loading of server resources. The article shows that the dynamic load balancing algorithm, based on nonlinear approaches and predictive models, allows solving load distribution problems between servers of data center clusters more efficiently than traditional methods. The conclusion about the effectiveness of the developed algorithm is substantiated.
format	Статья
author	Mochalov, V. P. Мочалов, В. П. Bratchenko, N. Y. Братченко, Н. Ю. Gosteva, D. V. Гостева, Д. В.
author_facet	Mochalov, V. P. Мочалов, В. П. Bratchenko, N. Y. Братченко, Н. Ю. Gosteva, D. V. Гостева, Д. В.
author_sort	Mochalov, V. P.
title	Algorithm for Load Balancing of a Data Processing Center Based on a Nonlinear Forecast Model
title_short	Algorithm for Load Balancing of a Data Processing Center Based on a Nonlinear Forecast Model
title_full	Algorithm for Load Balancing of a Data Processing Center Based on a Nonlinear Forecast Model
title_fullStr	Algorithm for Load Balancing of a Data Processing Center Based on a Nonlinear Forecast Model
title_full_unstemmed	Algorithm for Load Balancing of a Data Processing Center Based on a Nonlinear Forecast Model
title_sort	algorithm for load balancing of a data processing center based on a nonlinear forecast model
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2024
url	https://dspace.ncfu.ru/handle/123456789/29324
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Algorithm for Load Balancing of a Data Processing Center Based on a Nonlinear Forecast Model

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