LOAD BALANCING OF THE LAYERS IoT FOG-CLOUD SUPPORT NETWORK

• Published in: Сучасні інформаційні системи Vol. 9; no. 1; pp. 91 - 98
• Main Authors: Kuchuk, Heorhii, Husieva, Yuliia, Novoselov, Sergiy, Lysytsia, Dmytro, Krykhovetskyi, Heorhii
• Format: Journal Article
• Language: English
• Published: National Technical University "Kharkiv Polytechnic Institute" 24.02.2025
• Subjects: cloud environment; computer system; energy consumption; fog and edge computing; Internet of Things; mobile devices
• ISSN: 2522-9052
• DOI: 10.20998/2522-9052.2025.1.11

Topicality. Nowadays, the concept of the Internet of Things (IoT) is developing rapidly. In recent years, mobile devices have been used as elements of the IoT. But when using mobile devices, a number of problems arise. The main ones are the following: – limited computing resources; the need to maintain an energy-saving mode. Therefore, there is a need to balance the distribution of resources between all layers of the IoT support network. In this case, it is necessary to comply with all the time and structural constraints imposed by the IoT system with mobile devices. The subject of study in the article is methods of distributing IoT tasks between support network layers. The purpose of the article is to reduce the energy consumption of mobile IoT devices. The reduction occurs by transferring part of the load of mobile devices from the edge layer of the IoT support network. Time limits on IoT transactions must also be enforced. The following results were obtained. A model of the mobile computing unloading process has been developed. Proposed approach to calculating the average response time for components of different layers of the IoT support network: mobile device, fog node, cloud computing node. The task of choosing the optimal energy consumption option for mobile devices in the IoT support network is formulated. Conclusion. The dependence of the probability of unloading tasks from mobile IoT devices on the unloading threshold was analyzed. The conditions under which the minimum energy consumption is obtained when meeting time requirements were determined.