CFP last date
20 May 2024
Reseach Article

GBG Approach for Connectivity and Coverage Control in Wireless Sensor Network

by Buddha Singh, Haider Raza, Ritu
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 16 - Number 3
Year of Publication: 2011
Authors: Buddha Singh, Haider Raza, Ritu
10.5120/1994-2688

Buddha Singh, Haider Raza, Ritu . GBG Approach for Connectivity and Coverage Control in Wireless Sensor Network. International Journal of Computer Applications. 16, 3 ( February 2011), 13-18. DOI=10.5120/1994-2688

@article{ 10.5120/1994-2688,
author = { Buddha Singh, Haider Raza, Ritu },
title = { GBG Approach for Connectivity and Coverage Control in Wireless Sensor Network },
journal = { International Journal of Computer Applications },
issue_date = { February 2011 },
volume = { 16 },
number = { 3 },
month = { February },
year = { 2011 },
issn = { 0975-8887 },
pages = { 13-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume16/number3/1994-2688/ },
doi = { 10.5120/1994-2688 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:04:19.783438+05:30
%A Buddha Singh
%A Haider Raza
%A Ritu
%T GBG Approach for Connectivity and Coverage Control in Wireless Sensor Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 16
%N 3
%P 13-18
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Wireless sensor network are used to monitor various physical environment. These environments are mostly highly asymmetric terrains. The deployment of the sensor node for coverage and connectivity cost should be optimized. Therefore, in sensor network, providing high connectivity and coverage becomes the critical issue. In the proposed work, coverage and connectivity is a minimization of cost function as square of the distance between the nodes. This has been solved for cost optimization which is based on gradient methods. This modified protocol provides a genetic framework. We assume that the backbone nodes are connected to each and they provide coverage to the sensors on the basis of fitness function. The protocol performing better on the basis of cost which is also optimizing both network coverage and backbone connectivity. Our formalization allows the design of self-organized network system, which achieves minimum cost configurations. We have presented simulation results that show the effectiveness of genetic algorithm to provide network configuration that optimize both network coverage and backbone connectivity in different scenarios. We have simulated the Genetic Based Gradient (GBG) method and the proposed work in done on MATLAB.

References
  1. Jaime Liorca, Mehdi kalantari, Stuart D Milner, Christopher C Davis, “A quadratic optimization method for coverage and connectivity control in backbone based wireless sensor networks” IEEE-ISSNIP July 2007, pp 04-25
  2. P.Gupta, P. R. Kumar, “The capacity of wireless sensor networks” ,IEEE Trans.Inform. Theory, Vol. 46, No.2,2000,pp.388-404.
  3. Davis, C., Z. Haas, and S. Milner, “On How To Circumvent The Manet Scalability Curse” In: Proc. IEEE MILCOM, October 2006, pp. 1-7 .
  4. T.S. Rapport, wireless communications: principles and practice, prentice hall, Englewood cliffs, Nj.1996.
  5. Llorca, J., A. Desai. And S. Milner, “Obscuration Minimization in Dynamic Free Space Optical Networks through Topology Control”, In: Proc. IEEE MILCOM, 2004, Vol. 3, pp. 1247-1253.
  6. Azzedine Boukerche, and Xin Fei “A coverage-preserving scheme for wireless sensor network with irregular sensing range” Elsevier, Ad Hoc Networks(2007) 1303-1316
  7. Atumbe Jules Baruani. Network Engineering Using Multi-Objective Evolutionary Algorithms. Msc, Universit of Stellenbosch, 2007.
  8. WGBH Educational Foundation and Clear Blue Sky Productions. Summary of Darwin’s Theory of Evolution.
  9. Chakrabarty, K., Iyengar, S.S., Qi, H., Cho, E.: Grid Coverage for surveillance and target location in distributed sensork networks. In: IEEE Transactions on Computers.(2002) 51(12):1448-1453
  10. Hinojosa, Y., Puerto, J., Fern’andez, F.R.: A multiperiod two-echelon multicommodity capacitaded plant location problem. European Journal of Operational Research 123(2000) 271-291
  11. Genetic algorithms in search,optimization, and machine learning- David. Goldberg, Addison Wesley.
Index Terms

Computer Science
Information Sciences

Keywords

Genetic based gradient (GBG) Genetic Algorithm Coverage and Connectiviy