A dynamic-clustering reactive routing algorithm for wireless sensor networks
The clustering is a key routing method for large-scale wireless sensor networks, which effective extends the lifetime and the expansibility of network. In this paper, a node model is defined based on the structure and transmission principle of neuron, and a dynamic-clustering reactive routing algorithm is proposed. Once the event emergences, the cluster head is dynamic selected in the incident region according to the residual energy. The data collected by the cluster head is sent back to the Sink along the network backbone. Two kinds of accumulation ways are designed to increase the efficiency of data collection. Meanwhile through the fluctuation of action-threshold, the cluster head can trace the changing speed of incident; the nodes outside the incident region use this fluctuation to send data periodically. Finally, the simulation results verify that the DCRR algorithm extends the networks lifetime considerably and adapts to the change of network scale. The analysis shows that DCRR has more prominent advantages under low and middle load.
dynamic-clustering wireless sensor network neuron network backbone threshold