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MasterThesis on Congestion Detection in SDN networks using Machine Learning

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TCP Congestion Detection in Software-Define Networks using Machine Learning

Idea of this thesis is to detect congestion in SDN networks using decision tree algorithms

Tools used

  1. POX OpenFlow controller (Highly recommend to use Ryu Python based controller with OF ver 1.3 or 1.5).
  2. Mininet Emulator
  3. Wireshark
  4. Iperf ver. 3
  5. Bash scripting for GNU plot
  6. WEKA machine learning tool to train and test different decision tree algorithms
  7. Customized Linux Kernel

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MasterThesis on Congestion Detection in SDN networks using Machine Learning

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