A novel centralised clustering algorithm for energy efficient wireless sensor networks

  • Authors:

  • Stefano Colombo;Naveen Chilamkurti;Sherali Zeadally

  • Affiliations:

  • Polytecnico Di Torino, Corso Duca degli Abruzzi, 24 10129 Torino, Italy.;Computer Science and Computer Engineering, La Trobe University, Melbourne, Australia 3086.;Network Systems Laboratory, Department of Computer Science and Information Technology, University of the District of Columbia, Washington, DC 20008, USA

  • Venue:
  • International Journal of Autonomous and Adaptive Communications Systems
  • Year:
  • 2008

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Abstract

Wireless Sensor Networks (WSNs) consist of a large number oflow-power nodes sensing data from the environment. The sensor nodesare equipped with small and often irreplaceable batteries withlimited power capacity. One of the areas of sensor networking thathas attracted a lot of attention recently is the prolonging of thelife span of sensor networks by exploiting energy-efficient routingschemes. We propose a novel energy-efficient centralised clusteringalgorithm for WSN. The proposed algorithm generates a set ofpossible clustering alternatives from which it selects the optimalclustering. We also present a performance evaluation of theproposed algorithm using two performance metrics Max-min andMax-sum. We found that Max-sum yields superior performance. Inaddition, our proposed algorithm improves the system lifetimeperformance over Low Energy Adaptive Clustering Hierarchy-C byalmost 15%. We also compare performance results obtained with thechosen metric (Max-sum) with those obtained using other strategies(such as random and configuration 0). The Max-sum metricoutperforms the random and configuration 0 strategies by almost 8.5and 11%;, respectively, for system lifetime. Moreover, we foundthat the total amount of data collected using the Max-sum metric isat least 9% higher than with random and configuration 0strategies.