AI in NOC: A New Era for Capacity Planning and Network Management
Introduction :- Predicting router interface traffic in modern network management is critical to achieve optimal network performance, resource allocation, and proactively eliminate bottlenecks. This case study suggests using machine learning on network datasets to develop a model that predicts an actual router’s interface traffic versus an ideal router’s traffic. By evaluating historical data of network traffic and utilizing well-established machine learning API-based algorithms like Neural Networks, Decision Trees, and Ensemble Methods, this analysis reviews the formation possibilities of a strong prediction model with grand accuracy. At the end of the study, this paper reviews multiple factors and features related to the traffic in the interface such as the hour in the day, the day’s sequence in the week, the network protocol, the application, and the structure of the network. Additionally, it explores the machine learning algorithms to compare the accuracy of the ML model...