A hierarchical clustering algorithm based on spectral classification for Wireless Sensor Networks

A Wireless Sensor Network (WSN) is composed of a large number of autonomous and compact devices called sensor nodes. This network can be an effective tool for gathering data in a variety of environments. However, These sensor nodes have some constraints due to their limited energy, storage capacity and computing power. Therefor, saving energy and, thus extending the WSN lifetime entails great challenges. In order to prolong the lifetime of WSN, this study presents a hierarchical clustering algorithm based on spectral classification (HCA-SC). First, to overcome the ideal distribution of clusters, HCA-SC partition the network by spectral classification algorithm. Second, for each cluster, HCA-SC selects a node as a cluster head with regard residual energy and distance from base station. Simulation results showed that our algorithm performs better in reducing the energy consumption of sensor nodes and effectively improves the lifetime of wireless sensor networks.