Analyzing The Effect of Variable Round Time for Clustering Approach in Wireless Sensor Networks
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.
[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.
[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.
@article{"International Journal of Electrical, Electronic and Communication Sciences:52085", author = "Vipin Pal and Girdhari Singh and R P Yadav", title = "Analyzing The Effect of Variable Round Time for Clustering Approach in Wireless Sensor Networks", 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.", volume = "6", number = "11", pages = "1257-5", }