Spike neural network as a controller in SDN network


  • Anwar Dhyaa Majeed College of Engineering - University of Baghdad
  • Nadia Adnan Shiltagh Al-Jamali College of Engineering - University of Baghdad




Software Defined Network, spike neural networks, The Internet of Things, packet loss ratio, buffer utilization ratio


The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.


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How to Cite

Majeed, A. D. and Al-Jamali, N. A. S. (2021) “Spike neural network as a controller in SDN network”, Journal of Engineering, 27(9), pp. 64–77. doi: 10.31026/j.eng.2021.09.06.