Abstract
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.
Highlights
In recent years, it has become been widely expected to use software-defined networking (SDN) in wireless sensor networks (WSNs), so the WSNs' have great dynamic performance
This paper proposed a smart SDN controller by using multi spike neural network, in this work, 100 sensors randomly placed in a sensing area of square shape
The findings have shown that the Cicioglu et al, architecture proposed to perform better architecture proposed to perform better compared to the classical wireless body compared to the classical SDN controller area network architecture and meets the (QoS) requirements of IEEE / ISO
Summary
It has become been widely expected to use software-defined networking (SDN) in wireless sensor networks (WSNs), so the WSNs' have great dynamic performance. Kobo et al focused on the architecture view of software-defined networking in WSNs. The authors of (Jagadeesan et al.,2014, Haque et al, 2016) presented a section on SDN application in wireless networks. The authors of (Jagadeesan et al.,2014, Haque et al, 2016) presented a section on SDN application in wireless networks None of these sections sectioned what could be controlled by software-defined networking in WSNs and how applying software-defined networking in WSNs is dissimilar to wireline networks. It is essential to simplify sensing nodes' operation for saving power and managing wireless sensor networks with a robust controller having full vision over the whole network instead of distributed control protocols (Hayes, et al, 2016).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
