Model for determining a fog computing devices for a framework built on a microservice software platform

DOI: 10.31673/2412-9070.2026.017407

Abstract

The need to ensure the development of world economic relations, the intensive development of science and the strengthening of the defense sector require constant improvement and development of the information technology industry in the direction of increasing the speed and quality of useful data transmission. At the moment, the implementation of information and communication networks based on the concept of highly reliable communication with minimal delays (URLLC) is one of the most difficult tasks facing the scientific and technical community. The main requirement for URLLC class networks is high reliability of data transmission with minimal delays.
A key aspect of achieving these goals and ensuring these requirements is the effective use of software, which ultimately directly solves functional tasks, thereby generating the corresponding traffic of the telecommunications network.
The paper considers software built on the basis of the microservice architectural style of software development and implementation, which has been actively developing in the last 5–6 years.
The paper presents the results of solving one of the current tasks within the framework of the problem of implementing the microservice approach, namely, the development of a model for determining the fog computing device of a framework built on a microservice software platform.
A model for determining the fog computing device is presented, which, based on the technology of swarm intelligence algorithms - PSO (Particle Swarm Optimization), allows you to determine the potential of the target fog computing environment in order to select a Fog device to which it is advisable to migrate the corresponding microservice.
The results of the assessment of the applicability of the presented model, highlighted in the paper, showed its suitability for determining the fog computing device of a framework built on a microservice software platform.
It is shown that the use of the swarm intelligence algorithm (PSO) presented in the paper in the framework version proposed in the paper allows you to reduce the execution time of the microservice function by up to 70% due to the rational allocation of resources.

Keywords: framework; microservices software; fog computing devices; distributed fog dynamic computing.