An optimal clustering mechanism based on Fuzzy-C means for wireless sensor networks

In order to balance the node's energy consumption and extend the lifetime under energy-constrained wireless sensor networks, an energy-efficient clustering algorithm based on Fuzzy-C means for wireless sensor networks is proposed. Taking into account the uneven distribution of the sensor nodes and the uncertainty of the radio channel, the cluster formation process of nodes is modeled as a fuzzy partition of sample space in this paper. Firstly, the overall energy consumption of the networks is analyzed, and the optimal number of cluster heads is estimated based on node's density. Secondly, in the design of the objective function, the distance from the node to the cluster head and the weight of the membership values are considered. Then, the improved Fuzzy-C means clustering algorithm is proposed to divide the sensor nodes into a specified number of clusters. Finally, a single hop communication mode is used for intra cluster communication, and inter cluster communication adopts a multi-hop communication mode. The simulation results show that the proposed algorithm can obtain uniform spatial distribution of cluster heads and balance the energy consumption of network effectively.