Subscribe Now Subscribe Today
Research Article

Assistant Cluster Head Clustering Algorithm based on Cluster Grading in Wireless Sensor Networks

Zhang Ming

Clustering is an effective approach for organizing a network into a connected hierarchy, load balancing, and prolonging the network lifetime. In this study, an assistant cluster head clustering algorithm based on cluster grading (ACHC-CG) in wireless sensor networks was proposed, it has three obvious features: Firstly, using sensor density to divide each cluster into one of three grades, grade coefficient is an important parameter to generate assistant cluster head. Second, it utilizes residual energy, transmitting distance and historical data to dynamic generate assistant cluster head. Last, assistant cluster head is responsible for exchanging data between neighbor cluster heads, while cluster head is responsible for receiving sensing data in cluster and processing to reduce the energy consumption of head to prolong network lifetime and prolong the interval of generating cluster head. Simulation results show that, compared with LEACH, ACHC-CG significantly balances nodes average energy consumption and prolong the network lifetime.

Related Articles in ASCI
Similar Articles in this Journal
Search in Google Scholar
View Citation
Report Citation

  How to cite this article:

Zhang Ming , 2013. Assistant Cluster Head Clustering Algorithm based on Cluster Grading in Wireless Sensor Networks. Journal of Applied Sciences, 13: 1858-1864.

DOI: 10.3923/jas.2013.1858.1864


Abbasi, A.A. and M. Younis, 2007. A survey on clustering algorithms for wireless sensor networks. Comput. Commun., 30: 2826-2841.
CrossRef  |  Direct Link  |  

Bae, K. and H. Yoon, 2005. Autonomous clustering scheme for wireless sensor networks using coverage estimation-based self-pruning. IEICE Trans. Commun., 88: 973-980.
Direct Link  |  

Bajaber, F. and I. Awan, 2008. Dynamic/static clustering protocol for wireless sensor network. Proceedings of the 2nd UKSIM European Symposium on Computer Modeling and Simulation, September 8-10, 2008, Liverpool, UK., pp: 524-529.

Bandyopadhyay, S. and E.J. Coyle, 2003. An energy efficient hierarchical clustering algorithm for wireless sensor networks. Proceedings of the 22nd Annual Joint Conference of the Computer and Communications, Volume 3, March 30-April 3, 2003, San Franciso, CA., USA., pp: 1713-1723.

Boukerche, A., R.W.N. Pazzi and R.B Araujo, 2006. Fault-tolerant wireless sensor network routing protocols for the supervision of context-aware physical environments. J. Parallel Distrib. Comput., 66: 586-599.
CrossRef  |  Direct Link  |  

Chan, H. and A. Perrig, 2004. ACE: An emergent algorithm for highly uniform cluster formation. Proceedings of the 1st European Workshop on Sensor Networks, January 19-21, 2004, Berlin, Germany, pp: 154-171.

Chen, H., C.S. Wu, Y.S. Chu, C.C. Cheng and L.K. Tsai, 2007. Energy Residue Aware (ERA) clustering algorithm for leach-based wireless sensor networks. Proceedings of the 2nd International Conference on Systems and Networks Communications, August 25-31, 2007, Cap Esterel, France, pp: 40-47.

Deng, J., Y.S. Han, W.B. Heinzelman and P.K. Varshney, 2005. Scheduling sleeping nodes in high density cluster-based sensor networks. Mobile Networks Appl., 10: 825-835.
CrossRef  |  

Gao, Q., K.J. Blow, D.J. Holding, I.W. Marshall and X.H. Peng, 2006. Radio range adjustment for energy efficient wireless sensor networks. Ad Hoc Networks, 4: 75-82.
CrossRef  |  

Heinzelman, W.B., A.P. Chandrakasan and H. Balakrishnan, 2002. An application-specific protocol architecture for wireless microsensor networks. IEEE Trans. Wireless Commun., 1: 660-670.
CrossRef  |  Direct Link  |  

Heinzelman, W.R., A. Chandrakasan and H. Balakrishnan, 2000. Energy-efficient communication protocol for wireless microsensor networks. Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, January 4-7, 2000, Maui, HI., USA., pp: 1-10.

Kawadia, V. and P. Kumar, 2003. Power control and clustering in ad hoc networks. Proceedings of the 22th Annual Joint Conference of the IEEE Computer and Communications Societies, March 30-April 3, 2003, IEEE Xplore, London, pp: 459-469.

Li, C., M. Ye, G. Chen and J. Wu, 2005. An energy-efficient unequal clustering mechanism for wireless sensor networks. Proceedings of the International Conference on Mobile Adhoc and Sensor Systems Conference, November 7-10, 2005, Washington, DC., USA., pp: 1-8.

Liu, L.P., Z. Wang and Y.X. Sun, 2006. Survey on coverage in wireless sensor network deployment. J. Electron. Inform. Technol., 28: 1752-1757.

Nam, D.H. and H.K. Min, 2007. An efficient ad-hoc routing using a hybrid clustering method in a wireless sensor network. Proceedings of the 3rd IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, October 8-10, 2007, White Plains, NY., USA., pp: 60-.

Ran, G., H. Zhang and S. Gong, 2010. Improving on LEACH protocol of wireless sensor networks using fuzzy logic. J. Inform. Comput. Sci., 7: 767-775.
Direct Link  |  

Rocha, A.R., L. Pirmez, F.C. Delicato, E. Lemos, I. Santos, D.G. Gomes and J.N. de Souza, 2012. WSNs clustering based on semantic neighborhood relationships. Comput. Networks, 56: 1627-1645.
CrossRef  |  

Shu, T., M. Krunz and S. Vrudhula, 2005. Power balanced coverage-time optimization for clustered wireless sensor networks. Proceedings of the 6th ACM International Symposium on Mobile Ad Hoc Networking and Computing, May 25-28, 2005, Chicago, IL., USA., pp: 111-120.

Soro, S. and W.B. Heinzelman, 2005. Prolonging the lifetime of wireless sensor networks via unequal clustering. Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium, April 4-8, 2005, Denver, CO., USA., pp: 236-240.

Virrankoski, R. and A. Savvides, 2005. TASC: Topology adaptive spatial clustering for sensor networks. Proceedings of the IEEE International Conference on Mobile Adhoc and Sensor Systems, November 7, 2005, Washington DC., pp: 614-.

©  2019 Science Alert. All Rights Reserved