An application of LS-SVM method for clustering in wireless sensor networks

Abstract

We consider the problem of estimating the clustering of nodes in wireless sensor networks (WSNs). A solution to this problem is proposed, which uses Least Squares Support Vector Machines (LS-SVM). Using mixtures of kernels and the image energy distribution of the sensor field surface, we have been solved the clustering problem in WSNs. Some computer experiments for the simulated sensor fields are carried out. Through comparing with classical clustering scheme we state that LS-SVM method has a better improvement in clustering accuracy in these networks. © 2008 Springer-Verlag Berlin Heidelberg.