f52a864b-c7f3-44d3-8e69-0c1f49c22f1420230908085542735wseas:wseasmdt@crossref.orgMDT DepositWSEAS TRANSACTIONS ON COMPUTER RESEARCH2415-15211991-875510.37394/232018http://wseas.org/wseas/cms.action?id=13372214202321420231110.37394/232018.2023.11https://wseas.com/journals/cr/2023.phpNikitaShagovBasic Department of Digital Economy, Higher School of Cyber Technologies, Mathematics and Statistics, Plekhanov Russian University of Economics, RUSSIANataliaMamedovaBasic Department of Digital Economy, Higher School of Cyber Technologies, Mathematics and Statistics, Plekhanov Russian University of Economics, RUSSIAArkadiyUrintsovBasic Department of Digital Economy, Higher School of Cyber Technologies, Mathematics and Statistics, Plekhanov Russian University of Economics, RUSSIAThe existing gaps in approaches to the deployment of transport and logistics centers (TLC) within the edges of the backbone network lead to errors in the implementation of the spatial development strategy. Information support solutions for the implementation of terminal, transportation, and warehousing technologies are the least elaborated. As a result, errors have to be corrected in the process of operating the information architecture. There is a need to complement the existing TLC deployment management system with new tools that enhance the validity of TLC location assessment and eliminate the randomness factor in the choice of information architecture for TLC backbone network objects. This research aims to develop a flexible solution for network architecture design using cloud, fog, and edge layers. The main requirement for a flexible solution is that it can be rapidly deployed when the technology architecture changes. The proposed tool visualizes the structure of the network architecture and allows the analysis of information flows by capturing data on the movement of material cargo within the center and between TLC network facilities. The mapping tool considers the network computational load evaluation factor for the cloud, fog, and edge layers. The scientific novelty of the research results is achieved by the principle of system management of the components of complex systems. The practical significance of the results of the study lies in the possibility of using the mapping tool in the process of information architecture design at the stage of making decisions about the deployment of TLC network objects.97202397202324325222https://wseas.com/journals/cr/2023/a445118-174.pdf10.37394/232018.2023.11.22https://wseas.com/journals/cr/2023/a445118-174.pdf10.1016/j.future.2023.02.010E. Del-Pozo-Puñal, F. García-Carballeira, and D. Camarmas-Alonso, “A scalable simulator for cloud, fog and edge computing platforms with mobility support,” Futur. Gener. Comput. Syst., vol. 144, pp. 117–130, Jul. 2023, doi: 10.1016/J.FUTURE.2023.02.010. 10.1016/j.trpro.2023.02.107S. Bolgov, V. Haitbaev, and M. 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