№ 74-3 (том 2): ОБРАЗОВАНИЕ И НАУКА В XXI ВЕКЕ, Май, 2026
Научно-образовательные статьи

NETWORK QUALITY MONITORING SYSTEM

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  • Abdylov Eziz ,
  • Gylyjov Annamyrat
Abdylov Eziz
Oguz han Engineering and technology university of Turkmenistan
Gylyjov Annamyrat
Oguz han Engineering and technology university of Turkmenistan

Опубликован 28.05.2026

Ключевые слова

  • network quality monitoring; QoS; anomaly detection; real-time analytics; network performance; intelligent fault management; packet loss; latency; bandwidth management.

Как цитировать

E. Abdylov, & A. Gylyjov. (2026). NETWORK QUALITY MONITORING SYSTEM. ОБРАЗОВАНИЕ И НАУКА В XXI ВЕКЕ, 74-3 (том 2). https://mpcareer-google.ru/index.php/journal/article/view/5670

Аннотация

The rapid digitalization of modern infrastructure has made reliable network connectivity a mission-critical requirement across industries, public services, and everyday life. Despite advances in telecommunications, network performance degradation — manifesting as latency spikes, packet loss, jitter, and bandwidth congestion — continues to disrupt end-user experience and business continuity. This paper introduces and conceptualizes the Network Quality Monitoring System (NQMS), an intelligent, multi-layered platform designed to continuously observe, analyze, and report on network performance metrics in real time. Unlike conventional network management tools, the NQMS integrates machine learning-based anomaly detection, adaptive alerting, and predictive diagnostics to enable proactive quality assurance. The article examines the theoretical foundations of network performance monitoring, Quality of Service (QoS) frameworks, and intelligent fault management. We propose a three-layer architecture: data collection, analytics, and response layers. Furthermore, we discuss practical applications in enterprise networking, ISP management, and smart city infrastructure, alongside key challenges including data volume, heterogeneous environments, and security. Future research directions include AI-driven self-healing networks and federated monitoring across distributed systems.

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Библиографические ссылки

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