A New Clustering Algorithm in WSN Based on Spectral Clustering and Residual Energy
Ali Jorio, Sanaa El Fkihi, Brahim Elbhiri, Driss Aboutajdine · 2013
Wireless Sensor Networks (WSNs) are composed of large number of sensor nodes that are randomly distributed in a region of interest. The nodes are responsible of the supervision of a physical phenomenon and periodic transmission of results to the sink. Energy saving results in extending the life of the network, which presents a great challenge of WSNs. To deal with this, a hierarchical clustering scheme, called K-Way Spectral Clustering Algorithm in Wireless Sensor Network (KSCA-WSN), is proposed in this paper. This algorithm is based on spectral classification; it also considers the residual energy, as well as some properties of the network nodes. Thus, our approach aims to seek for an ideal distribution of sensor nodes (clusters) and proposes new feautures to elect the appropriate cluster-heads. In term of extending the network lifetime and minimizing the energy consumption, the simulation results show an important improvement of the network performances with KSCA-WSN compared to other existing clustering methods. Keywords-Clustering; Graph theory; Spectral classification; Energy consumption.