Improved Cuckoo Search-based Clustering Protocol for Wireless Sensor Networks

Subject Areas : Majlesi Journal of Telecommunication Devices

Hossein Sadeghian ¹ , Mohammadreza Soltan Aghaei ²

1 - software engineering
2 -

Received: 2019-04-15 Accepted : 2019-04-17 Published : 2019-06-01

Keywords: Wireless Sensor Networks, Clustering, cuckoo searc,

Abstract :

In most applications of intelligent networks equipped with wireless sensors, it is not possible to charge the nodes’ battery consistency and it is impossible under some conditions. Protocols designed for this type of networks should be energy efficient. The rapid consumption of battery power in wireless sensors and high power consumption in data transmission are two main challenges of this area. Nodes’ clustering is a natural way of categorizing nodes close together with the aim of using related data and removing plug-in data. However, existing clustering protocols are unbalanced in the term of energy consumption. The cluster heads are not distributed equally and overload clusters (with excess load) are much shorter than under-load clusters (low load). To solve this problem, an improved cuckoo search-based clustering algorithm (ICSCAS) has been proposed in present study. Also, performance evaluation of ICSCAS and its comparison with advanced clustering schemes in terms of total energy and residual energy consumption have been represented.

References:

[1] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “Wireless sensor networks: a survey," Computer Networks, vol. 38, pp. 393-422, 2002.

[2] Govind P. Gupta, Manoj Misra, Kumkum Garg, “Energy and trust aware mobile agent migration protocol for data aggregation in wireless sensor networks,” Journal of Network and Computer Applications, Volume 41, May 2014, pp. 300-311.

[3] Gupta, Govind P, “Efficient coverage and connectivity aware data gathering protocol for wireless sensor networks,” Recent Advances in Information Technology (RAIT), 3rd International Conference on. IEEE, 2016.

[4] W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy efficient communication protocol for wireless microsensor networks," in Proc. 33rd Annual Hawaii International Conf. Syst. Sciences, vol. 8, p. 8020, Hawaii, USA, Jan. 2000.

[5] O. Younis, S. Fahmy, “HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks,” IEEE Trans. Mobile Computing. Vol 3(4) , pp. 366–379, 2004.

[6] Adamu Murtala Zungeru, “Classical and swarm intelligence based routing protocols for wireless sensor networks: a survey and comparison,” Journal of Network and Computer Applications, vol. 35, pp. 1508–1536, 2012.

[7] Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. , “An application specific protocol architecture for wireless microsensor networks,” IEEE Transactions on Wireless Communications, vol. 1(4), pp. 660–670.

[8] Latiff, NM Abdul, Charalampos C. Tsimenidis, and Bayan S. Shari, “Energy-aware clustering for wireless sensor networks using particle swarm optimization.” IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications. IEEE, 2007.

[9] Kuila, P., & Jana, P. K., “A novel differential evolution based clustering algorithm for wireless sensor networks,” Applied Soft Computing, 25, 414–425, 2014.

[10] Lalwani, P., Banka, H. & Kumar, C., “BERA: a biogeography-based energy saving routing architecture for wireless sensor networks,” Soft Computing, pp 1–17, 2016.

[11] Mann, P.S. & Singh S., “Artificial bee colony metaheuristic for energy-efficient clustering and routing in wireless sensor networks,” Soft Computing, pp 1–14, 2016.

[12] RejinaParvin, J., and C. Vasanthanayaki, “Particle Swarm Optimization-Based Clustering by Preventing Residual Nodes in Wireless Sensor Networks,” IEEE Sensors Journal, 15.8, pp. 4264-4274, 2015.

[13] Rao, P. C., Jana, P. K., & Banka, H., “A particle swarm optimization based energy efficient cluster head selection algorithm for wireless sensor networks,” Wireless Networks, : 1-16, 2016.

[14] Adnan, Md. Akhtaruzzaman and Razzaque et al., “A Novel Cuckoo Search Based Clustering Algorithm for Wireless Sensor Networks”, Advanced Computer and Communication Engineering Technology: Proceedings of ICOCOE 2015", 2016, Springer International Publishing, 621-634.

[15] Yang, X.-S., & Deb, S., “Multi objective cuckoo search for design optimization,” Computers & Operations Research, 2011.

[16] Valian, E., & Valian, E., “A cuckoo search algorithm by Levy flights for solving reliability redundancy allocation problems,” Engineering Optimization, 1–14, 2012.

[17] Yang, X.-S., & Deb, S., “Cuckoo search: Recent advances and applications,” Neural Computing and Applications, 1–6, 2013.

[18] Gupta, G.P., ”Improved Cuckoo Search-based Clustering Protocol for Wireless Sensor Networks”. Procedia Computer Science, 2018. 125: p. 234-240.