Resource-aware technology of resource allocation informational process organizing in integrated Internet of things and edge computing concepts

The article is devoted to the development of a resource-oriented technology for organizing an information process of computational resource distribution under conditions of integrating the concepts of the Internet of Things (IoT) and edge computing. During the research, an analysis of existing models and methods was conducted and their shortcomings were identified, namely: the lack of consideration of the resource cost of data transit for computing nodes involved in data transmission and the computing process and the lack of consideration of the resource costs required for the operation of distributing computing resources. Given the limited resources of devices at the network edge, these drawbacks are particularly relevant. The goal of this study is to minimize resource consumption during resource distribution and solving computational tasks within systems constrained by device limitations. The foundation of the proposed technology includes: an overall mathematical model of resouce allocation process, formulated as an optimization problem; proposed methods for solving said problem based on heuristic rules and meta-heuristics; algorithms for calculating the resource cost of data transit and migration of computational tasks, which serve auxiliary purposes within the developed methods; a repository of meta-heuristic algorithms used to select the optimal method for solving the resource distribution problem. This technology implements the distribution of computational resources while minimizing resource expenses associated with data transit, taking into account both the computational task itself and decision-making regarding resource allocation. It considers the resource constraints of devices and dynamic changes in load and network topology. Experimental modeling confirmed the effectiveness of applying the proposed technology. Significant reductions in resource expenditure for computational resource distribution have been demonstrated, leading to improved results in terms of distributed computing efficiency metrics. The results of the study demonstrate the potential of the proposed technology for organizing distributed computing in systems with limited resources, such as IoT systems and edge computing.

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