Software control of the health of information systems in the energy industry to ensure functional stability

DOI: 10.31673/2409-7292.2024.020005

Abstract

Today, energy industry institutions are increasingly dependent on the functioning of information systems. Due to the rapid development of technologies, information systems are becoming increasingly complex and large-scale. They include a large number of components that interact with each other, and it is important to monitor their health and ensure their reliable operation and stability. The failure or disruption of such systems can lead to serious financial, social and technical problems. Considering these factors, the study of the process of monitoring the functioning parameters and control of the serviceable state of the information system is an urgent task. A system for monitoring functional parameters and controlling the serviceable state of power plant information system modules has been created based on a self-diagnosis algorithm using a test method to ensure functional stability. The system performs constant control of system elements using a test method with a wandering diagnostic core. In the event of a failure, damage or failure, the localization of the failed element is ensured, the system structure is changed by redistributing tasks to healthy nodes, information about the identified failures is issued to the system personnel to initiate the process of repair and restoration of the failed component of the information system. To confirm the correctness of the developed software product, mathematical modeling of the process of diagnosing the information system was carried out for different numbers of nodes. To analyze the results of the tests, a diagnostic reliability level is set, which serves as a sign of stopping the accumulation of test results in the memory of the module that will execute the specified algorithm.

Keywords: information system, database, monitoring, software, functional stability, external and internal destabilizing factors, diagnostics, test control, power plant, probability.