LLM-Based Algorithm Selection For Network Optimization and Orchestration

A modular LLM-based framework that uses contextual reasoning to dynamically select the most suitable optimization algorithm for real-time network orchestration. It addresses scaling challenges, reduces manual decision-making, and improves SLA-aware service partitioning across distributed infrastructures. Presented live at the SC25 Conference INDIS Workshop.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-15
DOI
https://doi.org/10.5281/zenodo.17801570
Primary Topic
Software-Defined Networks and 5G
Type
article
Field-Weighted Citation Impact
0.00
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article

LLM-Based Algorithm Selection For Network Optimization and Orchestration

Zenodo (CERN European Organization for Nuclear Research)
Software-Defined Networks and 5G
article

LLM-Based Algorithm Selection For Network Optimization and Orchestration

article en

Abstract

A modular LLM-based framework that uses contextual reasoning to dynamically select the most suitable optimization algorithm for real-time network orchestration. It addresses scaling challenges, reduces manual decision-making, and improves SLA-aware service partitioning across distributed infrastructures. Presented live at the SC25 Conference INDIS Workshop.

Zenodo (CERN European Organization for Nuclear Research)
University of Amsterdam (NL)
Industry, innovation and infrastructure
Openalex Percentile: Top 39%
Software-Defined Networks and 5G
DOIOpen Access PDFOpenAlex
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LLM-Based Algorithm Selection For Network Optimization and Orchestration · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS