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DMGEECA : Density Based Mean Grid Energy Efficient Clustering Algorithm For Mobile Wireless Sensor Networks
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DMGEECA : Density Based Mean Grid Energy Efficient Clustering Algorithm For Mobile Wireless Sensor Networks
K.J.C. Angel1 , E.G.D.P. Raj2
1 Dept. of Computer Science, Holy Cross College (Autonomous), Bharathidasan University, Tiruchirappalli, India.
2 School of Computer Science, Engineering and Applications, Bharathidasan University, Tiruchirappalli, India.
Correspondence should be addressed to: julietcatherine@yahoo.com.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-3 , Page no. 27-33, Mar-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i3.2733

Online published on Mar 30, 2018

Copyright © K.J.C. Angel, E.G.D.P. Raj . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 
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IEEE Style Citation: K.J.C. Angel, E.G.D.P. Raj, “DMGEECA : Density Based Mean Grid Energy Efficient Clustering Algorithm For Mobile Wireless Sensor Networks”, International Journal of Computer Sciences and Engineering, Vol.6, Issue.3, pp.27-33, 2018.

MLA Style Citation: K.J.C. Angel, E.G.D.P. Raj "DMGEECA : Density Based Mean Grid Energy Efficient Clustering Algorithm For Mobile Wireless Sensor Networks." International Journal of Computer Sciences and Engineering 6.3 (2018): 27-33.

APA Style Citation: K.J.C. Angel, E.G.D.P. Raj, (2018). DMGEECA : Density Based Mean Grid Energy Efficient Clustering Algorithm For Mobile Wireless Sensor Networks. International Journal of Computer Sciences and Engineering, 6(3), 27-33.
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Abstract :
Clustering is an important technique in Mobile Wireless Sensor Networks to reduce the communication overhead in several cases and reduce the energy consumption. In this paper, we propose a new clustering algorithm, DMGEECA(Density Based Mean Grid Energy Efficient Clustering Algorithm for Mobile Wireless Sensor Networks). The objective of our proposed algorithm is to elect a Cluster Head and increase the number of Cluster Heads based on the density of nodes in the area to reduce the energy consumption and thereby increasing the network lifetime. Simulations are carried out to evaluate the performance of our clustering algorithm by comparing its performance with the previous work. The results of simulation demonstrate that our proposed clustering algorithm outperforms the other algorithms in terms of Network Lifetime, Energy Consumption.
Key-Words / Index Term :
MWSNs, Clustering, Grid, Density, Mobility, Energy Efficiency
References :
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