The week's pick
Random Articles
Reseach Article
Computation of the Optimal Probability of becoming a Cluster Head in Hierarchical Clustered WSNs
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 75 - Number 1 |
| Year of Publication: 2013 |
| Authors: Mostafa Saadi, M. Lahcen Hasnaoui, Abderrahim Beni Hssane, Mohamed Laghdir |
10.5120/13072-0212
|
Mostafa Saadi, M. Lahcen Hasnaoui, Abderrahim Beni Hssane, Mohamed Laghdir . Computation of the Optimal Probability of becoming a Cluster Head in Hierarchical Clustered WSNs. International Journal of Computer Applications. 75, 1 ( August 2013), 1-7. DOI=10.5120/13072-0212
Abstract
Wireless Sensor Networks (WSNs) consist of a large number of energy-limited sensor nodes that are densely deployed in a large geographical region. The main challenge facing us in the design and conception of Wireless Sensor Networks (WSNs) is to find the best way to extend their life span. Therefore, proper energy management technics and communication protocols optimization have received increasing attention. The clustering algorithm is a key technique used to increase the scalability and life span of the network in general. In this paper, to generate clusters of sensors and reduce the cost of communication in them, we used a new approach from stochastic geometry as well as a distributed random algorithm. Moreover, we compute the optimal probability of becoming a cluster head in both cases rectangular and circular area. This study can successfully prolong the network's life span by reducing the total energy dissipation on the network and evenly distributing energy consumption over all sensor nodes. Our results could be used in any form of space deployment of sensors.
References
- F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirici. A survey on sensor networks. IEEE communications magazine, 40(8):pp. 102–114, 2002.
- Adrian Baddeley. Spatial point processes and their applications. Lecture Notes in Mathematics: Stochastic Geometry, Springer Verlag , Berlin Heidelberg, 2007.
- Seema Bandyopadhyay and E. J. Coyle. An energy efficient hierarchical clustering algorithm for wireless sensor networks. In Twenty-Second Annual Joint Conference of the IEEE Computer and Communications INFOCOM 2003, IEEE Societies, volume vol. 3, pages 1713 – 1723, april 2003.
- D. Estrin, L. Girod, G. Pottie, and M. Srivastava. Instrumenting the world with wireless sensor networks. In Proceedings of the International Conference on Acoustics, Speech and Signal Processing, (ICASSP 2001), pages vol. 4,pp. 2033– 2036, Salt Lake City, Utah, USA, May 2001.
- J. A. Fax and R. M. Murray. Information flow and cooperative control of vehicle formations. Automatic Control, IEEE Transactions on, 49(9):1465–1476, 2004.
- S. G. Foss and S. A. Zuyev. On a voronoi aggregative process related to a bivariate poisson process. In Adv. in Appl. Probab, pages 965–981, 1996.
- W. R. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan. Energyefficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS-33), Hawaii, USA, January 2000.
- W. R. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan. An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4):pp. 660–670, 2002.
- P. Holgate. The use of distance methods for the analysis of spatial distributions of points. Stochastic Point Processes, pages pp. 122–35, 1972.
- Chalermek Intanagonwiwat, Ramesh Govindan, and Deborah Estrin. Directed diffusion: a scalable and robust communication paradigm for sensor networks. In Proceedings of the 6th annual international conference on Mobile computing and networking, MobiCom '00, pages 56–67, New York, NY, USA, 2000. ACM.
- A. Jadbabaie, Jie Lin, and A. S. Morse. Coordination of groups of mobile autonomous agents using nearest neighbor rules. Automatic Control, IEEE Transactions on, 48(6):988–1001, 2003.
- S. Kar and J. M F Moura. Distributed average consensus in sensor networks with random link failures. In Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on, volume 2, pages II–1013–II– 1016, 2007.
- S. Karlin. A First Course in Stochastic Processes. Academic Press (USA), 1968.
- Nancy A. Lynch. Distributed Algorithms. Morgan Kaufmann Publishers Inc. , 1996.
- V. Mhatre, C. Rosenberg, D. Kofman, R. Mazumdar, and N. Shroff. Design of surveillance sensor grids with a lifetime constraint. In 1st EuropeanWorkshop onWireless Sensor Networks (EWSN), Berlin, January 2004.
- Atsuyuki Okabe, Barry Boots, and Kokichi Sugihara. Spatial tessellations: concepts and applications of Voronoi diagrams. John Wiley & Sons, Inc. , New York, NY, USA, 1992.
- R. Olfati-Saber, J. A. Fax, and R. M. Murray. Consensus and cooperation in networked multi-agent systems. Proceedings of the IEEE, 95(1):215–233, 2007.
- Li Qing, Qingxin Zhu, and Mingwen Wang. Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks. Computer Communication, 29(12):2230–2237, 2006.
- Wei Ren, R. W. Beard, and E. M. Atkins. A survey of consensus problems in multi-agent coordination. In American Control Conference, 2005. Proceedings of the 2005, pages 1859–1864 vol. 3, 2005.
- H. R. Thompson. Spatial point processes, with applications to ecology. Biometrika, 42:pp. 102– 115, 1955.
Index Terms
Keywords