Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/115637
Title: Using a Genetic Algorithm for Telemedicine Network Optimal Topology Synthesis
Author(s): Tsarоv, Roman
Nikityk, Lesya
Tymchenko, Iryna
Kumysh, Vladyslav
Shulakova, Kateryna
Siden, Serhii
Bodnar, Liliia
Granting Institution: Hochschule Anhalt
Issue Date: 2024
Language: English
Subjects: Informationstechnik
Datenverarbeitung
Abstract: A method based on a genetic algorithm is proposed for synthesizing the optimal topological structure of telemedicine network, ensuring that the distribution of users (with a known location) by telemedicine stations (the number and location of which are also known) is optimal in terms of signal delay time during transmission and the cost of network deployment. The method uses: random generating of a base population, a tournament selection of chromosomes among two pairs for crossover, and a homogeneous crossover operator. The results of benchmarking the proposed method are presented. The experiment reveals that the resulting solution is indeed close to optimal, i.e. due to the use of a genetic algorithm, the method avoids falling into the trap of a local extremum. While the current study focused on a specific telemedicine network, future research could explore the scalability of this genetic algorithm approach for larger-scale networks and consider additional factors such as energy efficiency and fault tolerance.
URI: https://opendata.uni-halle.de//handle/1981185920/117592
http://dx.doi.org/10.25673/115637
Open Access: Open access publication
License: (CC BY-SA 4.0) Creative Commons Attribution ShareAlike 4.0(CC BY-SA 4.0) Creative Commons Attribution ShareAlike 4.0
Appears in Collections:International Conference on Applied Innovations in IT (ICAIIT)

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