E.V. Glushak1, D.S. Klyuev2

1,2 Povolzhskiy State University of Telecommunications and Informatics (Samara, Russia)

1 evglushak@yandex.ru; 2 klyuevd@yandex.ru

Problem statement. With the development of the Internet of Things and the growth of data volumes, traditional cloud computing faces limitations such as high latency, network congestion and insufficient scalability. Foggy computing, by redistributing data processing closer to the sources of its generation, offers a solution to these problems. But their implementation requires the development of models that take into account device heterogeneity, computing resources, latency and data distribution. The main task is to optimize resource management, ensuring efficient distribution of calculations and minimizing energy consumption. It is becoming important to ensure the quality of service, including low latency and high reliability, which requires adaptive management methods. Therefore, it becomes relevant to analyze models and methods for the study and optimization of nebulous calculations that solve these problems.

The goal is to develop and analyze models and methods that effectively investigate, design and optimize cloud computing systems, taking into account their specifics, such as device heterogeneity, quality of service requirements, resource allocation management, and delay minimization.

Results. Patterns have been identified that can improve the distribution of tasks between nodes and reduce delays in data transmission. Resource optimization has shown effectiveness in improving the reliability of the system. The use of the developed models has made it possible to achieve a significant reduction in energy consumption without reducing productivity. The proposed approaches have made it possible to increase the stability and adaptability of foggy systems under changing loads and network conditions.

Practical significance. Development of models and methods that can be applied to design and optimize fog computing systems in real conditions, which will improve the quality of service by minimizing delays, efficiently allocating resources and improving system reliability. The proposed approaches can be used to develop sustainable infrastructures in areas such as the Internet of Things, where real-time data processing is required, which will ensure the adaptability and efficiency of foggy systems under varying loads and operating conditions.

Glushak E.V., Klyuev D.S. Development and research of models for the functioning of cloud and fog computing. Radiotekhnika. 2025. V. 89. № 3. P. 157−168. DOI: https://doi.org/10.18127/j00338486-202503-14 (In Russian)

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