Robust Energy Management Routing in WSN Using Neural Networks
Wireless Sensor Networks (WSNs) deployment process requires a continuous resource of energy. In this way, it become more important to monitor continuously the consumption of energy, trace where it is most required and utilized, and make a policy for uniform energy distribution at each node and energy efficient routing in WSNs. In this paper, the authors propose neural network based energy efficient routing path discovery and sensor energy management in WSNs with the objective of maximizing the network lifetime. Two experiments have been conducted with multi layered feed forward neural networks. One is used to predict the Most Significant Node in the network and another is used to determine the Group Head amongst the competitive sensor nodes.