Availability Assessment of a Cloud Server System: Comparing Markov and Semi-Markov Models

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Date
2021-09-22
Authors
Ivanchenko, O.
Kharchenko, V.
Moroz, B.
Ponochovnyi, Y. L.
Degtyareva, L. M.
Поночовний, Юрій Леонідович
Дегтярьова, Лариса Миколаївна
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Journal ISSN
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Publisher
Cracow, Poland
Abstract
Nowadays Markov Modelling Processes (MMP) found widely use into realm pertaining to availability assessments of diverse complex. technical systems and devices. In this regard, Cloud Server Systems (CSSs) are no exception. However, in order to leverage MMPs for the availability evaluation of CSSs the researchers should take into account that this assessmet procedure based on the utilization of just one distributio that is exponential distribution of times to failure, times 10 repair et prelit events and impacts. In that regard, that some groups of researchers into realm pertaining to CSSs availability are increasingly trying to leverage approaches based on Sem Markov Modelling Processes (SMMPs). Using SMMPs the researchers can consider more number of parametric characteristics and have a realistic picture as regards of availability level for the server system addition, seeking to improve overall availability of CSSs, the results for SMMPs in the so-called borders’ states, when Non-Markovian Process transforms at Markovian Process.
Description
O. Ivanchenko, V. Kharchenko, B. Moroz, Y. Ponochovnyi and L. Degtyareva, "Availability Assessment of a Cloud Server System: Comparing Markov and Semi-Markov Models," 2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 2021, pp. 1-6, doi: 10.1109/IDAACS53288.2021.9661052, , O. Ivanchenko, V. Kharchenko, B. Moroz, Y. Ponochovnyi, L. Degtyareva, "Availability Assessment of a Cloud Server System: Comparing Markov and Semi-Markov Models," 2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Crakow, Poland, 2021, pp. 1157-1162.
Keywords
Cloud Server System, Markov and Semi- Markov Modelling Processes, availabilty assessments
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