Cluster-head Election in Wireless Sensor Networks Using Fuzzy Logic



Electrical Engineering Department, Shahed University, Tehran, Iran


A wireless sensor network consists of many inexpensive sensor nodes that can be used toconfidently extract data from the environment .
Nodes are organized into clusters and in each cluster all non-cluster nodes transmit their data only to the cluster-head .The cluster-head transmits all received data to the base station .Because of energy limitation in sensor nodes and energy reduction in each data transmission, appropriate cluster-head election can significantly reduce energy consumption and enhance the life time of the network .In the proposed algorithm, a modified fuzzy logic approach is presented in order to improve the cluster-head election based on four descriptors energy, concentration, centrality and distance to base station .Cluster-head is elected by the base station in each round by calculating the chance each node has to elect as a cluster-head by considering descriptors .Network life time is evaluated based on first node dies metric, so energy depletion of one node causes the network to die .Simulation shows that theproposed algorithm can effectively increase the network life time .Sensor network is also simulated when sensor nodes move with random velocity in random direction in each round .Simulation shows that network life time is increased by considering this assumption in the proposed algorithm and can develop a better performance.


References [1] Q. Tian and E. Coyle, Optimal distributed detection in clustered wireless sensor networks, IEEE Trans. on Signal Processing, vol. 55, no. 7, pp. 3892-3904, 2007. [2] S. Lindsey, C. Raghavendra and K. Sivalingam, Data gathering algorithms in sensor networks using energy metrics, IEEE Trans. on Parallel and Distributed Systems, vol. 13, no. 9, pp. 924-935, 2002. [3] W. Heinzelman, A. Chandrakasan and H. Balakrishnan, An application-specific protocol architecture for wireless microsensor networks, IEEE Trans. on Wireless Communications, vol. 1, no. 4, pp. 660-670, 2002.
[4] F. Dressler, Self-Organization in ad hoc networks: overview and classification, University of Erlangen, Department of computer science 7, Technical report 02/06. [5] I. Gupta, D. Riordan and S. Sampalli, Cluster-head election using fuzzy logic for wireless sensor networks, Proc. of the 3rd Annual Communication Networks and Services Research Conf. , IEEE, pp. 238-243, 2005. [6] W. Heinzelman, A. Chandrakasan and H. Balakrishnan, Energy-efficient communication protocol for wireless microsensor networks, Proc. of the 33rd Annual Hawaii Int. Conf. on System Sciences, Maui, HI, pp. 3005-3014, Jan. 2000. [7] L. Wang, A course in fuzzy systems and control, Prentice-Hall, 1996. [8] C. M. Liu and C. H. Lee, Distributed algorithms for energy-efficient cluster-head election in wireless mobile sensor networks, Conf. on Wireless Networks (ICWN), pp. 405-411, 2005. [9] Q. Liang, Clusterhead election for mobile ad hoc wireless network, IEEE Int. Symp. on Personal, Indoor and Mobile Radio Communication Proceedings, vol. 2, pp. 1623-1628, 2003. [10] K. Yan, S.C. Wang, M. L. Chiang and L. Y. Tseng, A Fuzzy-based Power-aware management for mobile ad hoc networks, Computer standards & interfaces, pp. 123-136, 2008. [11] W. Zhenhua, H. Xiaodong, Z. Hong and L. Chang, Research on clustering strategy for wireless sensor network based on fuzzy theory, Springer-Verlag Berlin Heidelberg, pp. 596-604, 2007.
[12] K. M. Passino and S. Yurkovich, Fuzzy Control, Addison-wesley, 1998.
Volume 3, Issue 1 - Serial Number 1
January 2010
Pages 37-43
  • Receive Date: 14 April 2009
  • Revise Date: 05 November 2009
  • Accept Date: 12 November 2009
  • First Publish Date: 11 June 2012