A Dynamic-Clustering Reactive Routing Algorithm for Wireless Sensor Networks

The wireless sensor network is quite similar to neural network of human beings, which is a cluster of firmly related individual units and performs a special function. In this paper we propose a Dynamic-Clustering Reactive Routing algorithm based on Neural Structure (DCRR) according to the architecture and principle of neural network. The nodes in the network are driven by events. Temporary cluster-head is selected by nodes according to the similarity and isochronism of local on-the-spot data, then it is up to the temporary cluster-head to merge the data, by doing this the redundant messages are decreased efficiently as soon as possible. At the same time, we let the inspecting thresholds of each node change with data automatically. We compare the performance of DCRR with another reactive clustering algorithm, TEEN. The simulation results verify that the DCRR algorithm achieves significantly better balance in the battery power distribution and extends the network's lifetime considerably.