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Energy Efficient Data Aggregation using Voronoi based Genetic Clustering Algorithm in WSN

by S. Nithyakalyani, S. Suresh Kumar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 4
Year of Publication: 2012
Authors: S. Nithyakalyani, S. Suresh Kumar
10.5120/8556-2119

S. Nithyakalyani, S. Suresh Kumar . Energy Efficient Data Aggregation using Voronoi based Genetic Clustering Algorithm in WSN. International Journal of Computer Applications. 54, 4 ( September 2012), 37-41. DOI=10.5120/8556-2119

@article{ 10.5120/8556-2119,
author = { S. Nithyakalyani, S. Suresh Kumar },
title = { Energy Efficient Data Aggregation using Voronoi based Genetic Clustering Algorithm in WSN },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 4 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 37-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number4/8556-2119/ },
doi = { 10.5120/8556-2119 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:54:51.534947+05:30
%A S. Nithyakalyani
%A S. Suresh Kumar
%T Energy Efficient Data Aggregation using Voronoi based Genetic Clustering Algorithm in WSN
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 4
%P 37-41
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Wireless Sensor Network is an major emerging technique in wireless communication technology for application across a wide array of domains such as the military surveillance, medical diagnosis, weather forecasting, fire detection alarming systems, etc. One of the main challenges of wireless sensor network (WSN) is how to improve its time of livelihood due to the restricted energy of sensor nodes. Data must be aggregated in order to avoid amounts of traffic in the network, limit the recourses and energy. To solve the above dilemmas , data mining process such as clustering and data aggregation is used . clustering is used to group the nodes where as data aggregation function like MIN,MAX,AVG is used for swabbing redundant data transmission and improves the life span of energy in wireless sensor network. In this paper a new approach related to Voronoi based Genetic clustering (VBGC) Algorithm is proposed for energy efficient data aggregation. Our algorithm achieves energy efficiency by reducing the number of data transmission in each round to cluster head and from it to Base station (BS) . The Base Station periodically executes the proposed algorithm to select new Cluster-Heads after a certain period of time. Simulation results reveal that our algorithm outperforms basic GA.

References
  1. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "Wireless sensor networks: A survey," Computer Networks, vol. 38, no. 4, pp. 393–422, March 2002.
  2. W. Heinzelman, A. Chandrakasan, and H. Balakrishnan,"Energy-efficient communication protocol for wireless microsensor networks," in Proc. of the 33rd Annual Hawaii International Conference on System Sciences, pp. 3005-3014, January 2000.
  3. A. Abbasi and M. Younis, "A survey on clustering algorithms for wireless sensor networks," Computer Communications, vol. 30, pp. 2826-2841, October 2007.
  4. W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, "An application-specific protocol architecture for wireless microsensor networks," IEEE Trans. on Wireless Communications, 2002, 1(4), pp. 660-670.
  5. 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, 2004.
  6. D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning,Addison Wesley, Reading, MA, 1989.
  7. K. Sastry, D. Goldberg, and G. Kendall, Genetic Algorithms. Chapter 4 of Introductory Tutorials in Optimization and Decision Support Techniques, (eds. E. Burke and G. Kendall), pp. 97–125, Kluwer, 2005.
  8. R. Khanna, H. Liu, and H. H. Chen, "Self-organization of sensor networks using genetic algorithm," IEEE ICC '06, pp. 3377-3382,June 2006.
  9. O. Islam, S. Hussain, and H. Zhang, "Genetic algorithm for nergy efficient clusters in wireless sensor networks," IEEE ITNG '07, pp. 147 – 154, 2007.
  10. J. Zhang, Y. Lin, C. Zhou, and J. Ouyang, "Optimal model for energy-efficient clustering in wireless sensor networks using global simulated annealing genetic algorithm," IEEE IITAW '8, pp. 656 –660, 2008.
  11. H. Seo, S. Oh, and C. Lee, "Evolutionary genetic algorithm for efficient clustering of wireless sensor networks," IEEE CCNC 2009,pp. 1 – 5, 2009
  12. Naeim Rahmani, Farhad Nematy et al" Node Placement for Maximum Coverage Based on Voronoi Diagram Using Genetic Algorithm in Wireless Sensor Networks", Australian Journal of Basic and Applied Sciences, 5(12): 3221-3232, 2011
  13. S. Nithya kalyani and S. Suresh kumar " Optimal clustering Algorithm for Energy Efficient data Aggregation in WSN" European Journal of Scientific Research, ISSN 1450-216X Vol. 78 No. 1, ), pp. 146-155,2012.
Index Terms

Computer Science
Information Sciences

Keywords

Wireless Sensor Networks Voronoi Diagram Genetic Algorithm clustering data aggregation

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