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Erschienen in: Cluster Computing 5/2019

24.11.2017

Cat swarm algorithm in wireless sensor networks for optimized cluster head selection: a real time approach

verfasst von: D. Chandirasekaran, T. Jayabarathi

Erschienen in: Cluster Computing | Sonderheft 5/2019

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Abstract

The life time extension in the wireless sensor network (WSN) is the major concern in real time application, if the battery attached with the sensor node life is not optimized properly then the network life fall short. A protocol using a new evolutionary technique, cat swarm optimization (CSO), is designed and implemented in real time to minimize the intra-cluster distances between the cluster members and their cluster heads and optimize the energy distribution for the WSNs. We analyzed the performance of WSN protocol with the help of sensor nodes deployed in a field and grouped in to clusters. The novelty in our proposed scheme is considering the received signal strength, residual battery voltage and intra cluster distance of sensor nodes in cluster head selection with the help of CSO. The result is compared with the well-known protocol Low-energy adaptive clustering hierarchy-centralized (LEACH-C) and the swarm based optimization technique Particle swarm optimization (PSO). It was found that the battery energy level has been increased considerably of the traditional LEACH and PSO algorithm.

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Literatur
1.
Zurück zum Zitat Baronti, Paolo, et al.: Wireless sensor networks: a survey on the state of the art and the 802.15. 4 and ZigBee standards. Comput. Commun. 30(7), 1655–1695 (2007)CrossRef Baronti, Paolo, et al.: Wireless sensor networks: a survey on the state of the art and the 802.15. 4 and ZigBee standards. Comput. Commun. 30(7), 1655–1695 (2007)CrossRef
2.
Zurück zum Zitat Zhang, B., Simon, R., Aydin, H.: Harvesting-aware energy management for time-critical wireless sensor networks with joint voltage and modulation scaling. IEEE Trans. Ind. Inf. 9(1), 514–526 (2013)CrossRef Zhang, B., Simon, R., Aydin, H.: Harvesting-aware energy management for time-critical wireless sensor networks with joint voltage and modulation scaling. IEEE Trans. Ind. Inf. 9(1), 514–526 (2013)CrossRef
3.
Zurück zum Zitat Tan, Y.K., Panda, S.K.: Self-autonomous wireless sensor nodes with wind energy harvesting for remote sensing of wind-driven wildfire spread. IEEE Trans. Instrum. Meas. 60(4), 1367–1377 (2011)CrossRef Tan, Y.K., Panda, S.K.: Self-autonomous wireless sensor nodes with wind energy harvesting for remote sensing of wind-driven wildfire spread. IEEE Trans. Instrum. Meas. 60(4), 1367–1377 (2011)CrossRef
4.
Zurück zum Zitat Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensornetworks. System sciences, 2000. In: IEEE Proceedings of the 33rd Annual Hawaii International Conference (2000) Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensornetworks. System sciences, 2000. In: IEEE Proceedings of the 33rd Annual Hawaii International Conference (2000)
5.
Zurück zum Zitat Heinzelman, W.B.: Application-specific protocol architectures for wireless networks. Diss. Massachusetts Institute of Technology (2000) Heinzelman, W.B.: Application-specific protocol architectures for wireless networks. Diss. Massachusetts Institute of Technology (2000)
6.
Zurück zum Zitat Lindsey, S., Raghavendra, C.S.: PEGASIS: power-efficient gathering in sensor information systems. In: IEEE Aerospace Conference Proceedings, vol. 3 (2002) Lindsey, S., Raghavendra, C.S.: PEGASIS: power-efficient gathering in sensor information systems. In: IEEE Aerospace Conference Proceedings, vol. 3 (2002)
7.
Zurück zum Zitat Younis, O., Fahmy, S.: HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans. Mob. Comput. 3(4), 366–379 (2004)CrossRef Younis, O., Fahmy, S.: HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans. Mob. Comput. 3(4), 366–379 (2004)CrossRef
8.
Zurück zum Zitat Wang, J., et al.: An energy efficient stable election-based routing algorithm for wireless sensor networks. Sensors 13(11), 14301–14320 (2013)CrossRef Wang, J., et al.: An energy efficient stable election-based routing algorithm for wireless sensor networks. Sensors 13(11), 14301–14320 (2013)CrossRef
9.
Zurück zum Zitat Kannan, G., SreeRenga, R.T.: Energy efficient distributed cluster head scheduling scheme for two tiered wireless sensor network. Egypt. Inform. J. 16, 167–174 (2015)CrossRef Kannan, G., SreeRenga, R.T.: Energy efficient distributed cluster head scheduling scheme for two tiered wireless sensor network. Egypt. Inform. J. 16, 167–174 (2015)CrossRef
10.
Zurück zum Zitat Amgoth, T., Jana, P.K.: Energy-aware routing algorithm for wireless sensor networks. Comput. Electr. Eng. 41, 357–367 (2015)CrossRef Amgoth, T., Jana, P.K.: Energy-aware routing algorithm for wireless sensor networks. Comput. Electr. Eng. 41, 357–367 (2015)CrossRef
11.
Zurück zum Zitat Kuila, P., Jana, P.K.: A novel differential evolution based clustering algorithm for wireless sensor networks. Appl. Soft Comput. 25, 414–425 (2014)CrossRef Kuila, P., Jana, P.K.: A novel differential evolution based clustering algorithm for wireless sensor networks. Appl. Soft Comput. 25, 414–425 (2014)CrossRef
12.
Zurück zum Zitat Latiff, N.M., Tsimenidis, C.C., Sharif, B.S.: Energy-aware clustering for wireless sensor networks using particle swarm optimization. Personal, indoor and mobile radio communications, 2007. PIMRC 2007. In: IEEE 18th International Symposium (2007) Latiff, N.M., Tsimenidis, C.C., Sharif, B.S.: Energy-aware clustering for wireless sensor networks using particle swarm optimization. Personal, indoor and mobile radio communications, 2007. PIMRC 2007. In: IEEE 18th International Symposium (2007)
13.
Zurück zum Zitat Singh, B., Lobiyal, D.K.: Energy-aware cluster head selection using particle swarm optimization and analysis of packet retransmissions in WSN. Proced. Technol. 4, 171–176 (2012)CrossRef Singh, B., Lobiyal, D.K.: Energy-aware cluster head selection using particle swarm optimization and analysis of packet retransmissions in WSN. Proced. Technol. 4, 171–176 (2012)CrossRef
14.
Zurück zum Zitat Siew, Z.W., et al.: Cluster heads distribution of wireless sensor networks via adaptive Particle Swarm Optimization. In: Computational Intelligence, Communication Systems and Networks (CICSyN), 2012 IEEE Fourth International Conference (2012) Siew, Z.W., et al.: Cluster heads distribution of wireless sensor networks via adaptive Particle Swarm Optimization. In: Computational Intelligence, Communication Systems and Networks (CICSyN), 2012 IEEE Fourth International Conference (2012)
15.
Zurück zum Zitat Karaboga, Dervis, Okdem, Selcuk, Ozturk, Celal: Cluster based wireless sensor network routing using artificial bee colony algorithm. Wirel. Netw. 18(7), 847–860 (2012)CrossRef Karaboga, Dervis, Okdem, Selcuk, Ozturk, Celal: Cluster based wireless sensor network routing using artificial bee colony algorithm. Wirel. Netw. 18(7), 847–860 (2012)CrossRef
16.
Zurück zum Zitat Hoang, DucChinh, et al.: Real-time implementation of a harmony search algorithm-based clustering protocol for energy-efficient wireless sensor networks. IEEE Trans. Ind. Inform. 10(1), 774–783 (2014)MathSciNetCrossRef Hoang, DucChinh, et al.: Real-time implementation of a harmony search algorithm-based clustering protocol for energy-efficient wireless sensor networks. IEEE Trans. Ind. Inform. 10(1), 774–783 (2014)MathSciNetCrossRef
17.
Zurück zum Zitat Kong, L., et al.: An energy-aware routing protocol using cat swarm optimization for wireless sensor networks. Advanced Technologies, Embedded and Multimedia for Human-Centric Computing. Springer, Netherlands, pp. 311–318 (2014) Kong, L., et al.: An energy-aware routing protocol using cat swarm optimization for wireless sensor networks. Advanced Technologies, Embedded and Multimedia for Human-Centric Computing. Springer, Netherlands, pp. 311–318 (2014)
18.
Zurück zum Zitat Kong, L., et al.: A balanced power consumption algorithm based on enhanced parallel cat swarm optimization for wireless sensor network. Int. J. Distrib. Sens. Netw. 11, 729680 (2015)CrossRef Kong, L., et al.: A balanced power consumption algorithm based on enhanced parallel cat swarm optimization for wireless sensor network. Int. J. Distrib. Sens. Netw. 11, 729680 (2015)CrossRef
19.
Zurück zum Zitat Chu, S.-C., Tsai, P.-W.: Computational intelligence based on the behavior of cats. Int. J. Innov. Comput. Inf. Control 3(1), 163–173 (2007) Chu, S.-C., Tsai, P.-W.: Computational intelligence based on the behavior of cats. Int. J. Innov. Comput. Inf. Control 3(1), 163–173 (2007)
20.
Zurück zum Zitat Chu, S.-C., Tsai, P.-W., Pan, J.-S.: Cat Swarm Optimization. PRICAI 2006: Trends in Artificial Intelligence. Springer, Berlin, vol. 2006, pp. 854–858 (2006) Chu, S.-C., Tsai, P.-W., Pan, J.-S.: Cat Swarm Optimization. PRICAI 2006: Trends in Artificial Intelligence. Springer, Berlin, vol. 2006, pp. 854–858 (2006)
21.
Zurück zum Zitat Santosa, B., Ningrum, M.K.: Cat swarm optimization for clustering. Soft computing and pattern recognition, 2009. SOCPAR’09. In: International Conference of IEEE (2009) Santosa, B., Ningrum, M.K.: Cat swarm optimization for clustering. Soft computing and pattern recognition, 2009. SOCPAR’09. In: International Conference of IEEE (2009)
24.
Zurück zum Zitat Yan, R., Sun, H., Qian, Y.: Energy-aware sensor node design with its application in wireless sensor networks. IEEE Trans. Instrum. Meas. 62(5), 1183–1191 (2013)CrossRef Yan, R., Sun, H., Qian, Y.: Energy-aware sensor node design with its application in wireless sensor networks. IEEE Trans. Instrum. Meas. 62(5), 1183–1191 (2013)CrossRef
Metadaten
Titel
Cat swarm algorithm in wireless sensor networks for optimized cluster head selection: a real time approach
verfasst von
D. Chandirasekaran
T. Jayabarathi
Publikationsdatum
24.11.2017
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe Sonderheft 5/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-1392-4

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