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Influence of Packet Switching and Routing Methods on the Reliability of the Data Transmission Network and the Application of Artificial Neural Networks

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Intelligent Human Computer Interaction (IHCI 2022)

Abstract

In this article, a study was made of the influence of packet switching and routing methods on the reliability of a packet-switched data transmission network. Methods for routing and calculating the reliability of data transmission networks are considered. Analytical expressions for the readiness factor of communication channels between the nodes of the simulated network in virtual mode are given, as well as in the presence of redundancy, analytical expressions for the readiness factor of communication channels between the nodes of the simulated network in the datagram mode. Calculations of the reliability of data transmission networks with packet switching in the virtual mode and in the datagram mode are presented.

The features of the use of artificial neural networks in predicting the reliability of data transmission networks are considered. The scope of artificial neural networks is constantly expanding. In telecommunication systems, they are used in solving the following important problems: switching control, adaptive routing, traffic control, optimal distribution of network channel load, information encoding/decoding, etc. An algorithm for managing a data transmission network based on artificial neural networks is shown. The use of this algorithm for predicting the reliability indicators of telecommunication networks is proposed.

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Correspondence to D. Davronbekov .

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Davronbekov, D., Aripov, J., Jabbarov, S., Djuraev, R., Matkurbonov, D. (2023). Influence of Packet Switching and Routing Methods on the Reliability of the Data Transmission Network and the Application of Artificial Neural Networks. In: Zaynidinov, H., Singh, M., Tiwary, U.S., Singh, D. (eds) Intelligent Human Computer Interaction. IHCI 2022. Lecture Notes in Computer Science, vol 13741. Springer, Cham. https://doi.org/10.1007/978-3-031-27199-1_29

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  • DOI: https://doi.org/10.1007/978-3-031-27199-1_29

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