Low-Energy Dynamic Clustering Scheme for Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSNs) are mainly used to collaboratively sense and process information in the monitoring area. Sensor nodes have limited energy and are inconvenient to be replaced when the monitoring area is remote or dangerous. That makes the energy consumption an important problem for WSNs. For heterogeneous network, where sensor nodes have different energy, existing clustering methods only consider single factor, heterogeneity of node energy, for head selection. This paper applies fuzzy logic to consider multiple factors for clustering with the purpose of prolonging the lifetime of the network. Important factors, such as relative density of nodes in the network and the relative distance from the nodes to the base station, are considered together with the initial energy to select the cluster head dynamically. Simulation results demonstrated that proposed clustering algorithm can balance the energy consumption of the nodes in network and effectively prolong the survival time of the network, thus ensuring the accuracy of data aggregation.