Method for Choosing a Balanced Set of Fault-Tolerance Techniques for Distributed Computer Systems

We consider the problem of choosing a balanced set of fault-tolerance techniques for distributed computer systems. In this problem, it is necessary to choose a balanced set of versions of the modules of distributed computer systems, during which the reliability of the set must be maximized under cos...

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Vydáno v:Automatic control and computer sciences Ročník 51; číslo 7; s. 539 - 550
Hlavní autor: Volkanov, D. Yu
Médium: Journal Article
Jazyk:angličtina
Vydáno: Moscow Pleiades Publishing 01.12.2017
Springer Nature B.V
Témata:
Computer Science
Computer simulation
Control Structures and Microprogramming
Evolutionary algorithms
Fault tolerance
Fuzzy logic
Genetic algorithms
genetic algorithm
fault-tolerance
computer systems
reliability
fault-tolerance techniques
reliability optimization problem
evolutionary algorithm
ISSN:0146-4116, 1558-108X
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Shrnutí:We consider the problem of choosing a balanced set of fault-tolerance techniques for distributed computer systems. In this problem, it is necessary to choose a balanced set of versions of the modules of distributed computer systems, during which the reliability of the set must be maximized under cost constraints (on the set of possible versions of distributed computer systems). We describe the fault-tolerance techniques out of which the choice is made and consider a mathematical model in the context of which the formulation of the problem and the method of its solution are given. This problem is widely considered in the literature. A detailed description of the method for choosing a balanced set of fault-tolerance techniques for distributed computer systems is presented. The proposed method represents an evolutionary algorithm using the scheme of fuzzy logic. The scheme of fuzzy logic in the process of operating the algorithm analyzes the results of its operation in each generation and from this information adjusts the parameters of the evolutionary algorithm. The method makes it possible to obtain an efficient solution, as shown in the experimental research. A key feature of the proposed approach is the use of an adaptive scheme. The method has been implemented as software integrated with the DYANA simulation environment. The conclusions of the paper contain a brief description of future research directions.
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ISSN:0146-4116
1558-108X
DOI:10.3103/S0146411617070239