UNIVERSITY OF RUSE "ANGEL KANCHEV"
UNION OF SCIENTISTS - RUSE

Proceedings 2025
Faculty of Electrical and Electronic Engineering and AutomationBook 3.2 · Communication and Computer Technologies

FRI-2G.302-1-CCT2-01

ANALYTICAL INSTRUMENTS FOR NETWORK TRAFFIC DIAGNOSTICS IN COMMUNICATIONS

Language: ENPages: 75-84

Cite this paper

Assoc. Prof. Ivelina Balabanova, PhD

Department of Communications Equipment and Technologies Technical University of Gabrovo, Bulgaria

E-mail: ivstoeva@abv.bg

Assoc. Prof. Georgi Georgiev, PhD

Department of Communications Equipment and Technologies Technical University of Gabrovo, Bulgaria

E-mail: givanow@abv.bg

Abstract

In recent years, the digital evolution of Artificial Intelligence (AI) and Machine Learning (ML) has created a fundamental analytical framework to support technological innovation activities in various industry sectors. The paper presents a review on the integration of AI and ML concepts in monitoring and diagnostic systems in ICT- based infrastructures. A classification of the models, methods, algorithms and phases of different types of Machine Learning tools is made. Approaches for extracting of informative features when processing objects and processes using Artificial Intelligence technology are synthesized. A categorization of intelligent tools for analyzing the state of network traffic and performance indices of the transmission medium in communications was compiled. The review covers three analytical aspects in raw data manipulation procedures, respectively clustering, classification and predictive analysis.

Keywords

Transmission Medium, Network Traffic Monitoring, Artificial Intelligence, Machine Learning, Deep Learning

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