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Statistical Analysis of 5G Network Latency Based on Density-Based Clustering Method

  • Yiğit Kaan Bozkurt
  • , Ibraheem Shayea*
  • , Abdulraqeb Alhammadi
  • , Zhetkerbay Askhat
  • *Bu çalışma için yazışmadan sorumlu yazar
  • Istanbul Technical University
  • Universiti Teknologi Malaysia
  • Astana IT University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

Özet

This study explores the relationship between user density and the performance of fifth generation (5G) networks, focusing on latency behavior within a specific region using a large internet dataset. The analysis employs clustering techniques to determine network density and statistical modeling to evaluate latency dynamics. Results highlight a weak and statistically insignificant correlation between user density and latency, influenced by clustering methodology, dataset scope, and advancements in 5G traffic management technologies. The findings emphasize the importance of incorporating diverse and larger datasets, along with more sophisticated clustering methodologies, to accurately evaluate and enhance 5G network performance, particularly under conditions of varying user density.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıSelected Papers from the International Conference on Artificial Intelligence - FICAILY2025 - Current Research, Industry Trends, and Innovations
EditörlerAli Othman Albaji
YayınlayanSpringer Science and Business Media Deutschland GmbH
Sayfalar736-750
Sayfa sayısı15
ISBN (Basılı)9783032002310
DOI'lar
Yayın durumuYayınlandı - 2026
EtkinlikInternational Conference on AI: Current Research, Industry Trends, and Innovations, FICAILY 2025 - Tripoli, Libya
Süre: 9 Tem 202510 Tem 2025

Yayın serisi

AdıStudies in Computational Intelligence
Hacim1229 SCI
ISSN (Basılı)1860-949X
ISSN (Elektronik)1860-9503

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???event.eventtypes.event.conference???International Conference on AI: Current Research, Industry Trends, and Innovations, FICAILY 2025
Ülke/BölgeLibya
ŞehirTripoli
Periyot9/07/2510/07/25

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Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

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