Eradicate Energy Inefficiencies That Reduce The Lifetime Using Clustering Approach For WSN

International Journal of Computer Trends and Technology (IJCTT)          
© - Issue 2013 by IJCTT Journal
Volume-4 Issue-3                           
Year of Publication : 2013
Authors :Kush Bhushanwar, Praveen Bhanodia, Makrand Samvatsar


Kush Bhushanwar, Praveen Bhanodia, Makrand Samvatsar"Eradicate Energy Inefficiencies That Reduce The Lifetime Using Clustering Approach For WSN"International Journal of Computer Trends and Technology (IJCTT),V4(3):213-218 Issue 2013 .ISSN Published by Seventh Sense Research Group.

Abstract: - The wireless sensor network technology is a enter constituent for everywhere. A wireless sensor network consists of a huge number of sensor nodes. Every sensor node senses ecological circumstances such as temperature, force and light and sends the sensed data to a base station which is a long way off in general. Since the sensor nodes are powered by limited power batteries, in order to prolong the life time of the network, low energy consumption is important for sensor nodes. In universal, radio communication consumes the majority amount of energy, which is proportional to the data size and proportional to the square or the fourth power of the distance. We organized to reduce the energy consumption. In this paper, we studied classic clustering algorithms in wireless sensor networks and find two main reasons causing unnecessary energy consumption, which are fixed operation periods and too much information exchanged in cluster-heads selection. We proposed two types of clustering methods with less communication overhead for clustering. Based on federal management in k-means algorithm effective clustering and distributed approach.


[1] Jin-Shyan Lee, Wei-Liang Cheng,” Fuzzy-Logic-Based Clustering Approach for Wireless Sensor Networks Using Energy Predication” IEEE SENSORS JOURNAL, VOL. 12, NO. 9, SEPTEMBER 2012.
[2] Sampath Priyankara, Kazuhiko Kinoshita, Hideki Tode, and Koso Murakami, “A Clustering Method for Wireless Sensor Networks with Heterogeneous Node Types,” 18th International Conference on Computer Communications and Networks (IEEE ICCCN 2009), Aug. 2009.
[3] Kyuhong Lee and Heesang Lee,” EECR: Energy Efficient Clustering and Routing Approach for Wireless Sensor Networks” 978-1-4577-1088-9/11 IEEE-2011.
[4]Noritaka Shigei, Hiromi Miyajima, Hiroki Morishita, Michiharu Maeda,” Centralized and Distributed Clustering Methods for Energy Efficient Wireless Sensor Networks” Proceedings of the International MultiConference of Engineers and Computer Scientists 2009 Vol IMECS 2009, March 18 - 20, 2009, Hong Kong.
[5] W. Heinzelman, et. al., An application-specific protocol architecture for wireless microsensor networks," IEEE Transactions on Wireless Communications, 1(4):660-669, 2002.
[6] Q. Xue, A. Ganz, "Maximizing Sensor Network Lifetime: Analysis and Design Guides", in Proceedings of MILCOM, October 2004.
[7] s. Basagni, "Distributed Clustering Algorithm for Ad-hoc Networks" ,Proceedings of International Symposium on Parallel Architectures,Algorithms, and Neworks(ISPAN), 1999.

Keywords— adaptive period, residual energy, clustering algorithm, wireless sensor network.