LUCA: An Energy-efficient Unequal Clustering Algorithm Using Location Information for Wireless Sensor Networks

Abstract

Over the last several years, various clustering algorithms for wireless sensor networks have been proposed to prolong network lifetime. Most clustering algorithms provide an equal cluster size using node's ID, degree and etc. However, many of these algorithms heuristically determine the cluster size, even though the cluster size significantly affects the energy consumption of the entire network. In this paper, we present a theoretical model and propose a simple clustering algorithm called Location-based Unequal Clustering Algorithm (LUCA), where each cluster has a different cluster size based on its location information which is the distance between a cluster head and a sink. In LUCA, in order to minimize the energy consumption of entire network, a cluster has a larger cluster size as increasing distance from the sink. Simulation results show that LUCA achieves better performance than conventional equal clustering algorithm for energy efficiency.