Trends in Network Optimization Using Large Language Models 


Vol. 50,  No. 7, pp. 1073-1084, Jul.  2025
10.7840/kics.2025.50.7.1073


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  Abstract

Large Language Models (LLMs) are at the forefront of innovation across diverse domains, including network optimization, edge and distributed computing, and autonomous systems. This paper examines the critical role of LLMs in enhancing network management and optimization, enabling efficient edge and distributed computing, and advancing autonomous systems and control. It also evaluates their impact on performance improvement across these areas. Despite their significant potential, LLMs face several challenges, such as security vulnerabilities, limited energy efficiency, and inadequate integration of multimodal data. To overcome these limitations, this paper proposes a range of future research directions. With continued research and development, LLMs are poised to become foundational technologies across industries, enabling their full potential to be realized.

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[IEEE Style]

S. B. Son, J. Kim, C. Cho, S. Park, "Trends in Network Optimization Using Large Language Models," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 7, pp. 1073-1084, 2025. DOI: 10.7840/kics.2025.50.7.1073.

[ACM Style]

Seok Bin Son, Joongheon Kim, Changsik Cho, and Soohyun Park. 2025. Trends in Network Optimization Using Large Language Models. The Journal of Korean Institute of Communications and Information Sciences, 50, 7, (2025), 1073-1084. DOI: 10.7840/kics.2025.50.7.1073.

[KICS Style]

Seok Bin Son, Joongheon Kim, Changsik Cho, Soohyun Park, "Trends in Network Optimization Using Large Language Models," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 7, pp. 1073-1084, 7. 2025. (https://doi.org/10.7840/kics.2025.50.7.1073)
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