Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
Analyzing The Effect of Variable Round Time for Clustering Approach in Wireless Sensor Networks
Authors: Vipin Pal, Girdhari Singh, R P Yadav
Abstract:
As wireless sensor networks are energy constraint networks so energy efficiency of sensor nodes is the main design issue. Clustering of nodes is an energy efficient approach. It prolongs the lifetime of wireless sensor networks by avoiding long distance communication. Clustering algorithms operate in rounds. Performance of clustering algorithm depends upon the round time. A large round time consumes more energy of cluster heads while a small round time causes frequent re-clustering. So existing clustering algorithms apply a trade off to round time and calculate it from the initial parameters of networks. But it is not appropriate to use initial parameters based round time value throughout the network lifetime because wireless sensor networks are dynamic in nature (nodes can be added to the network or some nodes go out of energy). In this paper a variable round time approach is proposed that calculates round time depending upon the number of active nodes remaining in the field. The proposed approach makes the clustering algorithm adaptive to network dynamics. For simulation the approach is implemented with LEACH in NS-2 and the results show that there is 6% increase in network lifetime, 7% increase in 50% node death time and 5% improvement over the data units gathered at the base station.Keywords: Wireless Sensor Network, Clustering, Energy Efficiency, Round Time.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1058233
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1790References:
[1] I. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "Wireless sensor networks: a survey," Computer Networks, vol. 38, no. 4, pp. 393 - 422, 2002.
[2] D. Estrin, R. Govindan, J. S. Heidemann, and S. Kumar, "Next century challenges: Scalable coordination in sensor networks," in MOBICOM, 1999, pp. 263-270.
[3] A. Flammini, P. Ferrari, D. Marioli, E. Sisinni, and A. Taroni, "Wired and wireless sensor networks for industrial applications," Microelectron. J., vol. 40, no. 9, pp. 1322-1336, Sep. 2009.
[4] G. Anastasi, M. Conti, M. Di Francesco, and A. Passarella, "Energy conservation in wireless sensor networks: A survey," Ad Hoc Netw., vol. 7, no. 3, pp. 537-568, May 2009.
[5] A. A. Abbasi and M. Younis, "A survey on clustering algorithms for wireless sensor networks," Comput. Commun., vol. 30, no. 14-15, pp. 2826-2841, Oct. 2007.
[6] D. Wei and H. Chan, "Clustering ad hoc networks: Schemes and classifications," 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks, vol. 3, pp. 920-926, 2006.
[7] H. Karl and A. Willig, Protocols and architectures for wireless sensor networks. John Wiley & Sons, Oct. 2007.
[8] W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, "Energyefficient communication protocol for wireless microsensor networks," in Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8, ser. HICSS -00. Washington, DC, USA: IEEE Computer Society, 2000, pp. 8020-.
[9] K. Y. Jang, K. T. Kim, and H. Y. Youn, "An energy efficient routing scheme for wireless sensor networks," in International Conference on Computational Science and its Applications, ICCSA 2007., aug. 2007, pp. 399 -404.
[10] W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, "An application-specific protocol architecture for wireless microsensor networks," Wireless Communications, IEEE Transactions on, vol. 1, no. 4, pp. 660 - 670, oct 2002.
[11] T. Murata and H. Ishibuchi, "Performance evaluation of genetic algorithms for flowshop scheduling problems," in Proceedings of the First IEEE Conference on IEEE World Congress on Computational Intelligence, Evolutionary Computation, 1994., jun 1994, pp. 812 -817 vol.2.
[12] A. S. Zahmati, B. Abolhassani, A. Asghar, B. Shirazi, and A. S. Bakhtiari, "An energy-efficient protocol with static clustering for wireless sensor networks," 2007.
[13] S. Hussain and A. W. Matin, "Base station assisted hierarchical clusterbased routing," International Conference on Wireless and Mobile Communications, p. 9, 2006.
[14] F. Bajaber and I. Awan, "Adaptive decentralized re-clustering protocol for wireless sensor networks," J. Comput. Syst. Sci., vol. 77, no. 2, pp. 282-292, Mar. 2011.
[15] M. Liu, J. Cao, G. Chen, and X. Wang, "An energy-aware routing protocol in wireless sensor networks," Sensors, vol. 9, no. 1, pp. 445- 462, 2009.
[16] S. Ghiasi, A. Srivastava, X. Yang, and M. Sarrafzadeh, "Optimal energy aware clustering in sensor networks," Sensors, vol. 2, no. 7, pp. 258-269, 2002.
[17] F. K and V. K, "The network simulator ns-2," http:// www.isi.edu/nsnam/ns/.
[18] W. B. Heinzelman, "A low-energy protocol simulator for wireless networks," http:// www-mtl.mit.edu/research/icsystems/uamps.