Comprehensive performance criterion for hyper-converged infrastructure

DOI: 10.31673/2412-4338.2019.035562

Authors

  • Н. Г. Кучук, (Kuchuk N. H.) National Technical University «Kharkiv Polytechnic Institute», Kharkiv

Abstract

The purpose of the article: find a quantitative relationship between structural network parameters, an indicator of the efficiency of the use of resources and the quality of the services provided by the network for a network with hyperconverged infrastructure. The optimal values of the degree of load of the channels are obtained. For each link in a hyperconverged infrastructure network, the required number of transmission channels and the required throughput are calculated. This makes it possible to calculate the throughput of communication channels during network synthesis.

Keywords: hyperconvergence, performance criteria, channel loading.

References
1. Shmatkov S.I., Kuchuk, N.G. and Donets V.V. (2018). “Model of information structure of the hyperconvergent system of support of electronic computing resources of university e-learning”. Control systems, navigation and communication. PNTU. Poltava. 2 (48). 97-100. Print.
2. Merlac V., Smatkov S., Kuchuk N. and Nechausov A. (2018). “Resourses Distribution Method of University e-learning on the Hypercovergent platform”, Сonf. Proc. of 2018 IEEE 9th International Conference on Dependable Systems, Service and Technologies. DESSERT’2018, Ukraine, Kyiv. 136-140. Print. DOI: http://dx.doi.org/ 10.1109/DESSERT.2018.8409114
3. Donets V., Kuchuk N., Shmatkov S. (2018). “Development of software of e-learning information system synthesis modeling process”. Modern information systems. 2 (2). 117–121. Print. DOI: https://doi.org/10.20998/2522-9052.2018.2.20.
4. Kuchuk N., Mozhaiev O., Mozhaiev M. and Kuchuk H. (2017). “Method for calculating of R-learning traffic peakedness”, 4th International Scientific-Practical Conference Problems of Infocommunications Science and Technology, PIC S and T 2017. 359–362. Print. URL : http://dx.doi.org/10.1109/INFOCOMMST.2017.8246416
5. Kovalenko А. and Kuchuk H. (2018). “Methods for synthesis of informational and technical structures of critical application object’s control system”. Advanced Information Systems. 2 (1). 22–27. Print. DOI: https://doi.org/10.20998/2522-9052.2018.1.04
6. Sviridov A., Kovalenko A. and Kuchuk H. (2018), “The pass-through capacity redevelopment method of net critical section based on improvement ON/OFF models of traffic”, Advanced Information Systems, 2 (2). 139–144. Print. DOI: https://doi.org/10.20998/2522-9052.2018.2.24
7. Mozhaev O., Kuchuk H., Kuchuk N., Mozhaev M. and Lohvynenko M. (2017). “Multiservise network security metric”. IEEE Advanced information and communication technologies-2017. Proc. of the 2th Int. Conf.Lviv. 133-136. Print.
8. Kuchuk G., Kovalenko A., Komari I. E., Svyrydov A. and Kharchenko V. (2019). “Improving big data centers energy efficiency: Traffic based model and method”. Studies in Systems, Decision and Control, vol 171. Kharchenko, V., Kondratenko, Y., Kacprzyk, J. (Eds.). Springer Nature Switzerland AG. 161-183. Print. DOI: http://doi.org/10.1007/978-3-030-00253-4_8
9. Svyrydov A., Kuchuk H. and Tsiapa O. (2018). “Improving efficienty of image recognition process: Approach and case study”. Proceedings of 2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies, DESSERT 2018. 593-597. Print. DOI: http://dx.doi.org/10.1109/DESSERT.2018.8409201
10. Ruban I., Kuchuk H. and Kovalenko A. (2017). “Redistribution of base stations load in mobile communication networks”. Innovative technologies and scientific solutions for industries. 1 (1). 75-81. Print. DOI : https://doi.org/10.30837/2522-9818.2017.1.075
11. Amin Salih M. and Potrus M.Y. (2015). “A Method for Compensation of Tcp Throughput Degrading During Movement Of Mobile Node”, ZANCO Journal of Pure and Applied Sciences, 27 (6). 59–68. Print.
12. Mohammed, A. S. (2017). “Optimal Forecast Model for Erbil Traffic Road Data”, ZANCO Journal. 29 (5). 137–145, DOI: https://doi.org/10.21271/ZJPAS.29.5.15
13. Kuchuk G., Nechausov S. and Kharchenko V. (2015). “Two-stage optimization of resource allocation for hybrid cloud data store”. International Conference on Information and Digital Technologies. Zilina, 266-271. Print. DOI: http://dx.doi.org/10.1109/DT.2015.7222982
14. Sivaram M., Yuvaraj D., Amin Salih Mohammed, Porkodi V. and Manikandan V. (2018). “The Real Problem Through a Selection Making an Algorithm that Minimizes the Computational Complexity”, International Journal of Engineering and Advanced Technology, 8 (2). 95-100. Print.

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Published

2019-11-18

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