Ai-powered WI-FI access controllers: a new approach to wireless network design

Bondarchuk, Andrii та Korshun, Natalia та Dibrivnyi, Oles та Spivak, Svitlana (2025) Ai-powered WI-FI access controllers: a new approach to wireless network design Information and Telecommunication Sciences, 16 (2). с. 27-35. ISSN 2312-4121, 2411-2976

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Анотація

Background. Classical Wi-Fi architectures based on conventional access controllers are unable to provide stable, secure, and efficient wireless connectivity under modern conditions of high connection density and dynamic loads. This leads to frequent connection drops, inefficient use of network resources, and complicates proactive threat detection. As a result, organisations face decreased productivity, increased operational costs, and heightened cybersecurity risks. Objective. The aim of the article is to present an approach to designing Wi-Fi wireless networks using artificial intelligence and genetic algorithms, and to develop a comprehensive model and algorithm for multi-criteria optimisation of the network infrastructure. Methods. The research uses theoretical analysis of modern AI-based solutions, mathematical modelling of the access point placement optimisation problem, and the application of a genetic algorithm to find Pareto-optimal configurations. An original optimisation procedure is proposed, including stages of population generation, coverage assessment, fitness function calculation, and application of genetic operators. Results. An innovative mathematical approach for optimising access point placement is proposed, considering not only technical parameters but also architectural features of premises, quality of service (QoS), energy efficiency, and security. A comparative analysis of modern AI solutions from leading vendors (Juniper Mist AI, HPE Aruba Networking Central, Cisco DNA Center) is conducted. A closed-loop optimisation algorithm is developed, combining genetic algorithms for initial design and AI systems for dynamic network adaptation during operation. Conclusions. The research confirmed the high efficiency of integrating artificial intelligence and genetic algorithms for creating scalable, intelligent network infrastructures capable of real-time autonomous optimisation. The implementation of the proposed solutions significantly improves wireless communication quality, reduces operational costs, and ensures stable network performance under dynamic load conditions.

Тип елементу :	Стаття
Ключові слова:	wireless networks; artificial intelligence; Wi-Fi; genetic algorithms; coverage optimisation; AI access controllers
Типологія:	Статті у періодичних виданнях > Фахові (входять до переліку фахових, затверджений МОН) Статті у періодичних виданнях > Наукові рецензовані журнали (входять до інших баз, крім перерахованих та Google Academy, мають ISSN, DOI, індекс цитування)
Підрозділи:	Факультет інформаційних технологій та математики > Кафедра комп'ютерних наук
Користувач, що депонує:	Світлана Михайлівна Співак
Дата внесення:	02 Січ 2026 10:56
Останні зміни:	02 Січ 2026 12:50
URI:	https://elibrary.kubg.edu.ua/id/eprint/55771

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