Implementation of Machine Learning Algorithm in Preventing Network Congestion

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Noorazimah binti Ali Sabri
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In order to prevent the network congestion, many researchers has made further investigation to overcome or reduce this problem. The objective of this project is to implement machine learning algorithm in MPLS router to prevent network congestion and to perform an analysis of machine learning algorithm in MPLS router. This require a set of data. A dataset is collected to study the behaviour of the network with dynamic traffic properties with different network condition. A network topology is created based on the real network traffic and been observed with several conditions. The delay of every condition is observed by using Ostinato as the traffic and Wireshark to determine the time taken for every every networking path. Based from the network of several routers, Rapid Miner is used to predict the best machine learning model that have the fastest runtime with the lowest classification of error. The lowest delay will be the chosen route for the traffic. One of the main purpose is to forward the traffic in the lowest delay route in the network.
FYP 2 SEM 2 2019/2020
Machine Learning