Data Aggregation of Wireless Sensor Networks Using Artificial Neural Networks
Xia Meini · Chuangan jishu xuebao · 2011
To reduce communication traffic and save energy for wireless sensor networks(WSNs),BPNDA,a data aggregation algorithm based on back-propagation networks,was proposed,which integrates a three-layer BP neural network with clustering routing protocol.The input layer neuron is located in cluster members,while the hidden layer neuron and the output layer neuron are located in cluster head.Only the processed data represented the features of the raw collected data will be transmitted to the sink,so the efficiency of data gathering is improved and the lifetime of the network is prolonged.Simulation results show that compared with LEACH,the BPNDA algorithm effectively reduced the data traffic and decreased the energy dissipated of nodes.