Home // International Journal On Advances in Networks and Services, volume 7, numbers 3 and 4, 2014 // View article

Low Energy Adaptive Clustering in Wireless Sensor Network Based on Spectral Clustering

Authors:
Ali Jorio
Sanaa El Fkihi
Brahim Elbhiri
Driss Aboutajdine

Keywords: Wireless Sensor Network; Clustering; Graph theory; Spectral classification; Energy consumption.

Abstract:
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. This paper focuses primordially on reducing the power consumption of WSN. To deal with this, a hierarchical clustering scheme, called Multi-Relay K-way Spectral Clustering Algorithm (MR-KSCA), is proposed. This algorithm is based on spectral classification and graph theory with the aim to cluster the network in a fixed optimal number of clusters. Thus, our approach ensures an ideal distribution of sensor nodes in clusters, and proposes new features to elect the appropriate cluster-heads, which guarantee an uniform distribution load of energy among all the sensor nodes. Furthermore, We present three metrics to define the WSN lifetime. In term of extending the network lifetime and minimizing the energy consumption, the simulation results show an important improvement on the network performances with MR-KSCA compared to other existing clustering methods.

Pages: 138 to 147

Copyright: Copyright (c) to authors, 2014. Used with permission.

Publication date: December 30, 2014

Published in: journal

ISSN: 1942-2644