Adaptive Resource Allocation Method for the Mobile Fog Layer of High-Density Industrial Internet of Things in Industry 5.0 Networks

Relevance of the article. The modern concept of Industry 4.0 laid the foundation for complete digitalization through the industrial Internet of Things. However, the transition to Industry 5.0 requires greater flexibility and resilience of systems. High-density mobile industrial IoT with a fog layer is a critical element of this transformation, as it provides not only automation but also the adaptability of production to human needs and environmental standards. The object of study is the process of pre-processing transactions of the HDIoT edge layer. The main hypothesis of the study: the implementation of a new adaptive method of resource allocation for mobile devices of fog clusters will reduce the average pre-processing time of transactions of the HDIoT edge layer. The goal of the work is to reduce the average time a transaction of the HDIoT peripheral layer spends in the fog layer by developing an adaptive method for distributing the resources of mobile devices in fog clusters. Research objectives: to identify the architectural features of fog computing in HDIoT networks; to create a mathematical model of the process of optimal resource allocation for mobile cluster devices in the fog layer; to formalize a multi-agent approach to cluster resource allocation; to develop and investigate a theoretical game model for managing the resources of a mobile fog cluster of a multi-layer IoT. Methods used: multi-agent approach, game theory, in particular, optimization of a cooperative stochastic game, computer modeling. Results. An adaptive method for distributing resources of mobile devices in fog clusters has been developed. Within the framework of the method, the architecture of a mobile fog cluster has been proposed and a mathematical model of the process of optimal distribution of its resources has been created. In addition, a multi-agent approach is used to find an approximate solution to the formulated two-parameter nonlinear optimization problem, and a game-theoretical approach is implemented to reduce computational complexity and accelerate the search for an approximate solution. Conclusion. As a result of applying the developed method, the average time a transaction of the peripheral layer of a high-density IoT spends in the fog layer has been reduced, which, given the high density of mobile devices, has made it possible to meet QoS requirements.