Simulation environment for the choice of the decision making algorithm in multi-version real-time system

Abstract

Context: Nowadays the most effective way to improve the reliability of software is an approach with the introduction of software redundancy - multi-version programming. The reliability of a multi-version system is determined not only by the reliability of the versions that make it up, but to a greater degree by the decision making algorithm. Objective: Our objective is evaluation and selection of the most reliable voting algorithms in multi-version environments. In order to get this objective there is a need to check all the algorithms in the execution environment, simulating characteristic of the developed system. Thus, we obtain the characteristics of the quality of the algorithm operation in precisely those conditions in which it will work in the system that is developed. Method: The article suggests weighted voting algorithms with a forgetting element, as well as modifications of existing voting algorithms. To be able to check the quality of their work, the simulation environment has been implemented that simulates the operation of the software multi-version execution environment. Results: The article substantiates the use of the most reliable decision making algorithms in the decision block of the real-time operating system. A comparative analysis of decision making algorithms for the operation of the decision making block of the multi-version real-time execution environment has been carried out. Conclusions: The software implementation of the simulation environment that implements the simulations of versions with given characteristics is considered, not only classical decision making algorithms, but also the author's modifications are investigated. The environment allows to obtain the quality characteristics of all implemented decision making algorithms with given system characteristics. The modeling results are considered, the dependence of the system reliability indicators on its input parameters is shown, a comparative analysis of various decision making algorithms based on the modeling results is made.