MODIFIED TRAINING ALGORITHM FOR SPIKING NEURAL NETWORK AND ITS APPLICATION IN WIRELESS SENSOR NETWORK
Abstract: In this paper, controlling of data traffic of the Wireless Sensor Network (WSN) is implemented to improve the Quality of Service (QoS) in WSN with mobile sink node. The quality of service is measured in terms of throughput ratio, Packet Loss Ratio (PLR) and Network Energy Consumption (NEC). Spiking neural network is applied to implement the controller that is most suitable with changeable traffic data. The controller is implemented based on python simulation. Simulation results showed that the proposed controller provides better quality of service in comparison with wireless sensor network without controller by about 57%.
Keywords: Wireless Sensor Network, Congestion Control in Wireless Sensor Network, improve QoS in Wireless Sensor Network.
How to Cite:
[1] Mohammed Mousa Rashid Al-Yasari, Nadia Adnan Shiltagh Al-Jamali, “MODIFIED TRAINING ALGORITHM FOR SPIKING NEURAL NETWORK AND ITS APPLICATION IN WIRELESS SENSOR NETWORK,” International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2018.5105
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