Application Of Deep Neural Network Machine Learning Algorithm For End-To-End Congestion Control
- Author
- Muchenje Nigel
- Title
- Application Of Deep Neural Network Machine Learning Algorithm For End-To-End Congestion Control
- Abstract
-
Abstract
The system for Network Congestion Detection using Deep Neural Networks (DNNs) operates in a multi-stage process to effectively monitor and manage network traffic. Initially, the system collects real-time or historical network data, which is then pre-processed to remove noise and prepare it for analysis. In the training phase, this pre-processed data is used to train a DNN model, chosen from architectures like Convolutional Neural Networks (CNNs) or Recurrent Neural Networks (RNNs). This model is optimized iteratively using algorithms to enhance its ability to detect congestion patterns in the network
- Date
- JUNE 2024
- Publisher
- BUSE
- Keywords
- Network Congestion Detection using Deep Neural Networks (DNNs), monitor and manage network traffic. Recurrent Neural Networks (RNNs).
- Supervisor
- Mr Matombo
- Media
-
Nigel Muchenje
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