Full Article: PDF
Scientific Object Identifier: http://s-o-i.org/1.1/TAS-10-138-16
DOI: https://dx.doi.org/10.15863/TAS.2024.10.138.16
Language: Russian
Citation: Tiumentsev, D. (2024). The role of AI in network infrastructure automation. ISJ Theoretical & Applied Science, 10 (138), 157-163. Soi: http://s-o-i.org/1.1/TAS-10-138-16 Doi: https://dx.doi.org/10.15863/TAS.2024.10.138.16 |
Pages: 157-163
Published: 30.10.2024
Abstract: The article discusses the role of artificial intelligence (AI) in the automation of network infrastructure. It examines the capabilities of AI to automate processes such as network monitoring, status analysis, failure prediction, and routing optimization. The article analyzes modern technologies, including machine learning (ML), deep learning (DL), and natural language processing (NLP), which enable systems to quickly adapt to real-time changes and minimize human intervention. It is emphasized that the use of AI significantly improves network management efficiency and promotes the development of self-healing networks that can automatically recover from failures. The article also highlights the challenges of AI implementation, including the need for integration with legacy systems and ensuring data security. Successful examples of AI applications in network systems across various companies are reviewed, demonstrating its significant potential to enhance the reliability and resilience of infrastructure.
Key words: artificial intelligence, AI, automation, network infrastructure, machine learning, ML, deep learning, DL, self-healing networks.
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