Energy-efficient and scalable clustering scheme for wireless sensor networks

Abstract

Wireless sensor networks (WSNs), comprising a larger number of battery-powered sensor nodes for event monitoring and data gathering, have been widely deployed into various military and industrial applications. Since most of WSN applications aim to make full use of the energy-limited sensor nodes to monitor a wide area for a long time, energy efficiency and scalability become two important performance metrics for WSNs. Clustering has been proved to be an effective way to improve energy efficiency and network lifetime for WSNs. However, with the increasing scale of WSNs, existing clustering schemes would face significant limitations in improving energy efficiency and prolonging network lifetime. Inspired by the similar features between large scale WSNs and complex networks, some analysis methods in complex networks can be utilized to address these limitations. In this paper, we propose a clustering scheme, named Energy-aware and Scalable Clustering Scheme (ESCS), to enhance the energy efficiency and scalability in WSNs. The proposed scheme is based on the inherent characteristics of WSNs and evolution idea of Barabasi-Albert (BA) model. Extensive simulation results demonstrate that ESCS can prolong the network lifetime and significantly improve the scalability of WSNs.