Energy Efficient Clustering Algorithm with Global and Local Re-clustering for Wireless Sensor Networks
Wireless Sensor Networks consist of inexpensive, low power sensor nodes deployed to monitor the environment and collect data. Gathering information in an energy efficient manner is a critical aspect to prolong the network lifetime. Clustering algorithms have an advantage of enhancing the network lifetime. Current clustering algorithms usually focus on global re-clustering and local re-clustering separately. This paper, proposed a combination of those two reclustering methods to reduce the energy consumption of the network. Furthermore, the proposed algorithm can apply to homogeneous as well as heterogeneous wireless sensor networks. In addition, the cluster head rotation happens, only when its energy drops below a dynamic threshold value computed by the algorithm. The simulation result shows that the proposed algorithm prolong the network lifetime compared to existing algorithms.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1086869Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2127
 M. P. S. S. K. Singh and D. K. Singh, “Energy efficient homogenous clustering algorithm for wireless sensor networks,” International Journal of Wireless and Mobile Networks ( IJWMN ), Vol.2, No.3, , August 2010.
 S.Gamwarige and E.C.Kulasekere, “An energy efficient distributed clustering algorithm for ad-hoc deployed wireless sensor networks in building monitoring applications,” Electronic Journal of Structural Engineering (eJSE) Special Issue: Sensor Network on Building Monitoring: from Theory to Real Application, pp. 11–27, 2009.
 A. C. W. Heinzelman and H. Balakrishnan, “Energy-efficient communication protocol for wireless microsensor networks,” Proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS ’00), January 2000.
 I. M. G. Smaragdakis and A. Bestavros, “Sep: A stable election protocol for clustered heterogeneous wireless sensor networks,” Proceedings of the International Workshop on SANPA, (Boston), pp. 1–11, August 2004.
 O. Younis and S. Fahmy, “Heed: A hybrid, energy-efficient, distributed clustering approach for ad-hoc sensor networks,” IEEE Transactions on Mobile Computing, vol. 3, pp. 366–379, October-December 2004.
 Q. Z. Y. Wang and D. Zheng, “Energy-driven adaptive clustering data collection protocol in wireless sensor networks,” in Proceedings of the 2004 International Conference on Intelligent Mechatronics and Automation (ICIMA2004), (UESTC, Chengdu, China), pp. 599–604, August 2004.
 Y. Q. J. YU and G. WANG, “An energy-driven unequal clustering protocol for heterogeneous wireless sensor networks,” Journal of Control Theory and Applications, pp. 133–139, 2011.
 J. Chang, “An energy-aware cluster-based routing algorithm for wireless sensor networks,” ournal of Information Science and Engineering 26, pp. 2159–2171, 2010.
 G. C. C. Li, M. Ye and W. J, “An energy-efficient unequal clustering mechanism for wireless sensor networks,” IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, p. 604, 2005.
 H. J. De Silva, S. Gamwarige, and E. C. Kulasekere, “Energy expenditure of global reclustering and local delegation in wireless sensor networks,” in Wireless And Optical Communications Networks (WOCN), 2010 Seventh International Conference On, pp. 1–6, 2010.