INTELLIGENT MACHINE-LEARNING-BASED METHODS FOR QUALITY OF SERVICE ASSURANCE IN TELECOMMUNICATION NETWORKS
Keywords:
artificial intelligence, machine learning, quality of service, QoS, SLA, failure prediction, anomaly detection, network slicing, self-optimizing networks, 5G.Abstract
This paper systematizes intelligent methods for ensuring Quality of Service (QoS) in modern telecommunication networks. In contrast to a survey-level description of the application areas of artificial intelligence (AI), the emphasis is placed on specific classes of machine learning (ML) methods and their role in the transition from reactive to proactive network management: failure prediction and predictive maintenance, anomaly detection, network resource optimization and network slicing, as well as the formation of self-optimizing and autonomous networks. AI-based approaches to QoS/SLA management are reviewed, and the key challenges are outlined — data quality and privacy, model interpretability, and integration with existing management systems. It is concluded that intelligent methods are a necessary condition for ensuring sustainable quality of service in 5G and next-generation networks.
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