Management models of data collection processes in IoT networks with the dynamic structure
( Pp. 62-71)

The collection of data from the network with dynamic structure is a complex process that must be performed with considering of security, energy efficiency and latency requirements. To determine the optimal data collection models that meet the stated requirements, the authors analyzed models and methods of data collection in dynamic networks, as well as management processes of data collection. The study allows to determine the most effective technologies for data collection in dynamic networks, which include Fog technologies and clustering technologies. Based on the analysis, the authors have developed the model for data collection managment, which allows to construct and rebuild the structures of data collection models in accordance with the requirements and conditions of data collection. The developed approaches and principles were successfully implemented in practice: a system of data collection was tested for the crane complexes, which is designed to work at production sites. In general, the study allows to identify methods and tools that effectively solve the problems of data collection in the networks with dynamic structure, and to demonstrate the solution of these problems in practice.

Aung M.T., Abbas S.A., Zhukova N.A., Chernokulsky V.V., (2020), MANAGEMENT MODELS OF DATA COLLECTION PROCESSES IN IOT NETWORKS WITH THE DYNAMIC STRUCTURE. Computational Nanotechnology, 3 => 62-71.

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data collection process management, dynamic network, internet of things, computing systems, Fog technologies, management models of data collection.