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Neural Network Enabled WSN Management for Energy Efficient Routing Mechanism
Background/Objectives: To design a model for Wireless Sensor Network which manage the routing mechanism efficiently and reduce the power consumption during packet routing. Methods: Neural Network Approach e.g. Self-Organized Map and K-Means Algorithms used for cluster selection and election to improve the energy efficiency. Findings: Neural Networks algorithms in combination of cluster head load sharing and self-silence model provides a better performance than the existing Wireless Sensor Network routing protocols. Improvements/Applications: This design approach can be further enhanced through Fuzzy based neural network model.
Network, Neural WSN Routing, Reverse Transmission, Sensor Network, Sensor Cluster.
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