Efficient Energy Management Routing in WSN

In this proposal, a neural network
approach is proposed for energy conservation routing in
a wireless sensor network. Our designed neural network
system has been successfully applied to our scheme of
energy conservation. Neural network is applied to predict
Most Significant Node and selecting the Group Head
amongst the association of sensor nodes in the network.
After having a precise prediction about Most Significant
Node, we would like to expand our approach in future to
different WSN power management techniques and
observe the results. In this proposal, we used arbitrary
data for our experiment purpose; it is also expected to
generate a real time data for the experiment in future and
also by using adhoc networks the energy level of the node
can be maximized. The selection of Group Head is
proposed using neural network with feed forward
learning method. And the neural network found able to
select a node amongst competing nodes as Group Head.