Using a Genetic Algorithm for Telemedicine Network Optimal Topology Synthesis
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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Anhalt University of Applied Sciences
2024-03-01
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| Series: | Proceedings of the International Conference on Applied Innovations in IT |
| Subjects: | |
| Online Access: | https://icaiit.org/paper.php?paper=12th_ICAIIT_1/1_3 |
| _version_ | 1797201715818135552 |
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| author | Roman Tsarov Lesya Nikityk Iryna Tymchenko Vladyslav Kumysh Kateryna Shulakova Serhii Siden Liliia Bodnar |
| author_facet | Roman Tsarov Lesya Nikityk Iryna Tymchenko Vladyslav Kumysh Kateryna Shulakova Serhii Siden Liliia Bodnar |
| author_sort | Roman Tsarov |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-24T07:51:57Z |
| format | Article |
| id | doaj.art-3bdb27cdeb564b7ca75e4f2f3631bb19 |
| institution | Directory Open Access Journal |
| issn | 2199-8876 |
| language | English |
| last_indexed | 2024-04-24T07:51:57Z |
| publishDate | 2024-03-01 |
| publisher | Anhalt University of Applied Sciences |
| record_format | Article |
| series | Proceedings of the International Conference on Applied Innovations in IT |
| spelling | doaj.art-3bdb27cdeb564b7ca75e4f2f3631bb192024-04-18T10:00:16ZengAnhalt University of Applied SciencesProceedings of the International Conference on Applied Innovations in IT2199-88762024-03-011211924http://dx.doi.org/10.25673/115637Using a Genetic Algorithm for Telemedicine Network Optimal Topology SynthesisRoman Tsarov0https://orcid.org/0000-0001-9897-9672Lesya Nikityk1https://orcid.org/0000-0003-1777-8452Iryna Tymchenko2https://orcid.org/0009-0009-2903-7599Vladyslav Kumysh3https://orcid.org/0000-0002-6544-5081Kateryna Shulakova4https://orcid.org/0000-0002-0035-6184Serhii Siden5https://orcid.org/0000-0002-8708-0706Liliia Bodnar6https://orcid.org/0000-0001-9497-214XState University of Intelligent Technologies and Telecommunications, Kuznechna Str. 1, 65023 Odesa, UkraineState University of Intelligent Technologies and Telecommunications, Kuznechna Str. 1, 65023 Odesa, UkraineState University of Intelligent Technologies and Telecommunications, Kuznechna Str. 1, 65023 Odesa, UkraineVitalSource Technologies LLC, Fayetteville Str. 227, Suite 400, Raleigh, NC 27601, United StatesState University of Intelligent Technologies and Telecommunications, Kuznechna Str. 1, 65023 Odesa, Ukraine / Anhalt University of Applied Sciences, Bernburger Str. 57, 06366 Köthen, GermanyState University of Intelligent Technologies and Telecommunications, Kuznechna Str. 1, 65023 Odesa, UkraineSouth Ukrainian National Pedagogical University, Staroportofrankyvska Str. 26, 65020 Odesa, UkraineA 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.https://icaiit.org/paper.php?paper=12th_ICAIIT_1/1_3telemedicinetelemedicine networktopology synthesistopology optimizationgenetic algorithm |
| spellingShingle | Roman Tsarov Lesya Nikityk Iryna Tymchenko Vladyslav Kumysh Kateryna Shulakova Serhii Siden Liliia Bodnar Using a Genetic Algorithm for Telemedicine Network Optimal Topology Synthesis Proceedings of the International Conference on Applied Innovations in IT telemedicine telemedicine network topology synthesis topology optimization genetic algorithm |
| title | Using a Genetic Algorithm for Telemedicine Network Optimal Topology Synthesis |
| title_full | Using a Genetic Algorithm for Telemedicine Network Optimal Topology Synthesis |
| title_fullStr | Using a Genetic Algorithm for Telemedicine Network Optimal Topology Synthesis |
| title_full_unstemmed | Using a Genetic Algorithm for Telemedicine Network Optimal Topology Synthesis |
| title_short | Using a Genetic Algorithm for Telemedicine Network Optimal Topology Synthesis |
| title_sort | using a genetic algorithm for telemedicine network optimal topology synthesis |
| topic | telemedicine telemedicine network topology synthesis topology optimization genetic algorithm |
| url | https://icaiit.org/paper.php?paper=12th_ICAIIT_1/1_3 |
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