Extending the lifetime of a wireless sensor networks remains one of the prominent research topics in recent years. Clustering has been proven to be energy-efficient in sensor networks since data routing and relaying are only operated by cluster heads. The present paper focuses on proposing two algorithms. In the former nodes organize themselves into clusters using fuzzy c-means (FCM) mechanism then a randomly node chooses itself cluster head in each cluster since initially all nodes have the same amount of power. Then the node having the higher residual energy elects itself cluster head. All non-cluster head nodes transmit sensed data to the cluster head. This latter performs data aggregation and transmits the data directly to the remote base station. The second algorithm which is a improvement of the former uses the same principle in forming clusters and electing cluster heads but operates in multi-hop manner when it routes data from cluster heads to the base station. Simulation results show that the proposed algorithms improve energy consumption and consequently resulting in an extension of the network lifetime. In addition, the second algorithm proves its ability to be applied in large-scale wireless sensor networks.
| Published in | International Journal of Sensors and Sensor Networks (Volume 1, Issue 2) |
| DOI | 10.11648/j.ijssn.20130102.11 |
| Page(s) | 21-26 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Wireless Sensor Networks, Fuzzy C-Means, Clustering, Lifetime
| [1] | S. Olariu, "Information Assurance in Wireless sensor networks", Parallel and Distributed Processing Symposium. 19th IEEE International, April 2005. |
| [2] | G. Haosong and Y. Younghwan, "Distributed Bottleneck Node Detection in Wireless Sensor Networks", IEEE 10th International Conference on Computer and Information Technology (CIT), July 2010, pp. 218-224. |
| [3] | P. M. Wightmanl and M. A. Labrador, "Topology Maintenance: Extending the Lifetime of Wireless Sensor Networks", IEEE LATIN AMERICA TRANSACTIONS, Vol. 8, No. 4, Aug. 2010. |
| [4] | A. Boukerche, "Algorithms and Protocols for Wireless Sensor Networks", John Wiley & Sons, Inc, pp.161, 2009. |
| [5] | A. A. Abbasi and M. Younis, "A survey on clustering algorithms for wireless sensor networks", Elsevier, Computer Communications, 2007, pp. 2826–2841. |
| [6] | A. M, A. Boukerche and R. W. Nelem Pazzi, "A Taxonomy of Cluster-based Routing Protocols for Wireless Sensor Networks", IEEE International Symposium on Parallel Architectures, Algorithms, and Networks, pp. 247–253, 2008. |
| [7] | W. Heinzelman, A. Chadrakasan and H. Balakrishnan, "Energy efficient communication protocol for wireless microsensor networks", in Proceedings of the 33rd Annual HawaiII International Conference on System Sciences, Jan 4-7, 2000. |
| [8] | W.B. Heinzelman, A.P. Chandrakasan, H. Balakrishnan, "An application-specific protocol architecture for wireless microsensor networks", IEEE Transactions on Wireless Communications, Vol. 1, Issue 4, pp. 660-670, 2002. |
| [9] | Si-Ho Cha1 and Minho Jo, "An Energy-Efficient Clustering Algorithm for Large-Scale Wireless Sensor Networks", Advanced in Grid and Pervasive Computing, Vol. 4459, 2007, pp. 436–446. |
| [10] | O. Younis, S. Fahmy, "HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks", IEEE Transactions on Mobile Computing, Vol. 3, Issue 4, 2004, pp. 366-379. |
| [11] | M. Ye, C. Li, G. Chen, J. Wu, "An energy efficient clustering scheme in wireless sensor networks", 24th International Conference on Performance, Computing and Communication, 7-9 April 2005, pp. 535-540. |
| [12] | D.C. Hoang, R. Kumar and S.K. Panda, "Fuzzy C-Means Clustering Protocol for wireless sensor networks", IEEE International Symposium on Idustrial Electronics (ISIE), July 2010, pp. 3477-3482. |
| [13] | A. Manjeshwar and D. P. Agarwal, "TEEN: a Routing Protocol for Enhanced Efficiency in Wireless Sensor Networks", Parallel and Distributed Processing Symposium., Proceedings 15th International, 2001, pp. 2009-2015. |
| [14] | A. Manjeshwar and D. P. Agarwal, "APTEEN: a hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks", Parallel and Distributed Processing Symposium, Proceedings International, 2002, pp. 195-202. |
| [15] | H. Izakian, A. Abraham and V. Snasel, "Fuzzy Clustering Using Hybrid Fuzzy c-means and Fuzzy Particle Swarm Optimization", IEEE World Congress on Nature & Biologically Inspired Computing, USA, 2009, pp.1690-1694 |
APA Style
Mourad Hadjila, Hervé Guyennet, Mohammed Feham. (2013). Energy-Efficient in Wireless Sensor Networks using Fuzzy C-Means Clustering Approach. International Journal of Sensors and Sensor Networks, 1(2), 21-26. https://doi.org/10.11648/j.ijssn.20130102.11
ACS Style
Mourad Hadjila; Hervé Guyennet; Mohammed Feham. Energy-Efficient in Wireless Sensor Networks using Fuzzy C-Means Clustering Approach. Int. J. Sens. Sens. Netw. 2013, 1(2), 21-26. doi: 10.11648/j.ijssn.20130102.11
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Download@article{10.11648/j.ijssn.20130102.11,
author = {Mourad Hadjila and Hervé Guyennet and Mohammed Feham},
title = {Energy-Efficient in Wireless Sensor Networks using Fuzzy C-Means Clustering Approach},
journal = {International Journal of Sensors and Sensor Networks},
volume = {1},
number = {2},
pages = {21-26},
doi = {10.11648/j.ijssn.20130102.11},
url = {https://doi.org/10.11648/j.ijssn.20130102.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssn.20130102.11},
abstract = {Extending the lifetime of a wireless sensor networks remains one of the prominent research topics in recent years. Clustering has been proven to be energy-efficient in sensor networks since data routing and relaying are only operated by cluster heads. The present paper focuses on proposing two algorithms. In the former nodes organize themselves into clusters using fuzzy c-means (FCM) mechanism then a randomly node chooses itself cluster head in each cluster since initially all nodes have the same amount of power. Then the node having the higher residual energy elects itself cluster head. All non-cluster head nodes transmit sensed data to the cluster head. This latter performs data aggregation and transmits the data directly to the remote base station. The second algorithm which is a improvement of the former uses the same principle in forming clusters and electing cluster heads but operates in multi-hop manner when it routes data from cluster heads to the base station. Simulation results show that the proposed algorithms improve energy consumption and consequently resulting in an extension of the network lifetime. In addition, the second algorithm proves its ability to be applied in large-scale wireless sensor networks.},
year = {2013}
}
TY - JOUR T1 - Energy-Efficient in Wireless Sensor Networks using Fuzzy C-Means Clustering Approach AU - Mourad Hadjila AU - Hervé Guyennet AU - Mohammed Feham Y1 - 2013/04/02 PY - 2013 N1 - https://doi.org/10.11648/j.ijssn.20130102.11 DO - 10.11648/j.ijssn.20130102.11 T2 - International Journal of Sensors and Sensor Networks JF - International Journal of Sensors and Sensor Networks JO - International Journal of Sensors and Sensor Networks SP - 21 EP - 26 PB - Science Publishing Group SN - 2329-1788 UR - https://doi.org/10.11648/j.ijssn.20130102.11 AB - Extending the lifetime of a wireless sensor networks remains one of the prominent research topics in recent years. Clustering has been proven to be energy-efficient in sensor networks since data routing and relaying are only operated by cluster heads. The present paper focuses on proposing two algorithms. In the former nodes organize themselves into clusters using fuzzy c-means (FCM) mechanism then a randomly node chooses itself cluster head in each cluster since initially all nodes have the same amount of power. Then the node having the higher residual energy elects itself cluster head. All non-cluster head nodes transmit sensed data to the cluster head. This latter performs data aggregation and transmits the data directly to the remote base station. The second algorithm which is a improvement of the former uses the same principle in forming clusters and electing cluster heads but operates in multi-hop manner when it routes data from cluster heads to the base station. Simulation results show that the proposed algorithms improve energy consumption and consequently resulting in an extension of the network lifetime. In addition, the second algorithm proves its ability to be applied in large-scale wireless sensor networks. VL - 1 IS - 2 ER -
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