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Title: Algorithm for Determining the Optimal Weights for the Akushsky Core Function with an Approximate Rank
Authors: Shiriaev, E. M.
Ширяев, Е. М.
Kucherov, N. N.
Кучеров, Н. Н.
Babenko, M. G.
Бабенко, М. Г.
Lutsenko, V. V.
Луценко, В. В.
Keywords: Akushsky core function;Residue number system (RNS);Chinese remainder theorem;Fog computing;Monte Carlo method
Issue Date: 2023
Citation: Shiriaev, E., Kucherov, N., Babenko, M., Lutsenko, V., Al-Galda, S. Algorithm for Determining the Optimal Weights for the Akushsky Core Function with an Approximate Rank // Applied Sciences (Switzerland). - 2023. - 13 (18). - статья № 10495. - DOI: 10.3390/app131810495
Series/Report no.: Applied Sciences (Switzerland)
Abstract: In this paper, a study is carried out related to improving the reliability and fault tolerance of Fog Computing systems. This work is a continuation of previous studies. In the past, we have developed a method of fast operation for determining the sign of a number in the Residue Number System based on the Akushsky Core Function. We managed to increase the efficiency of calculations by using the approximate rank of a number. However, this result is not final. In this paper, we consider in detail the methods and techniques of the Akushsky Core Function. During research, it was found that the so-called weights can be equal to random variables. Based on the data obtained, we have developed a method for determining the optimal weights for the Akushsky Core Function. The result obtained allows you to obtain a performance advantage due to the preliminary identification of optimal weights for each set of moduli.
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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