Energy-Aware Routing in UWSNs Using Cuckoo Algorithms for Improving Network Lifetime

Musa Mojarad¹ , Fariba Sarhangnia² , Amin Rezaeipanah³

Section:Research Paper, Product Type: Journal-Paper
Vol.8 , Issue.3 , pp.1-5, Sep-2021

Online published on Sep 30, 2021

Copyright © Musa Mojarad, Fariba Sarhangnia, Amin Rezaeipanah . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Today, the use of Wireless Sensor Networks (WSNs) is increasingly growing. The WSN consists of a number of sensor nodes that are spread across an environment and communicate with each other to collect information about the target environment. Underwater Wireless Sensor Networks (UWSNs) are a type of sensor network that is located in the underwater environment and communicates with each other by sound waves. These networks have a big number of limited energy nodes scattered in a limited area. Due to the limited energy in this type of networks, increasing the lifetime by reducing energy consumption has always been considered. Most of the nodes’ energy is used to send information to the central station. Given that our country has long water borders in the Persian Gulf region, it is worthwhile to be able to monitor this environment. The aim of this paper is to present a cuckoo routing algorithm based on fuzzy clustering in order to properly distribute energy consumption. The results of the simulations indicate the benefit of the proposed method in the number of packets sent and the network lifetime compared to other similar methods. The results show an 18.13% advantage of the proposed algorithm in sending messages and also a 10.34% increase in network lifetime over the SH-FEER protocol.

Key-Words / Index Term :
Underwater Wireless Sensor Networks, Cuckoo Algorithm, Routing, Fuzzy Clustering

References :
[1] Nguyen, N. T., Le, T. T., Nguyen, H. H., & Voznak, M.. Energy-efficient clustering multi-hop routing protocol in a UWSN. Sensors, 21(2), 627, 2021.
[2] Ahmed, M., Salleh, M., Channa, M. I., & Rohani, M. F.. Energy efficient routing protocols for UWSN: A Review. Telkomnika, 15(1), 212, 2017.
[3] Wang, J., Shen, J., Shi, W., Qiao, G., Wu, S., & Wang, X.. A Novel Energy-Efficient Contention-Based MAC Protocol Used for OA-UWSN. Sensors, 19(1), 183, 2019.
[4] Prakash, P. S.. Machine Learning-Based Optimized Hierarchical Routing Protocols for WSN Lifetime: A Review. Information Technology In Industry, 9(2), 289-307, 2021.
[5] Prasanna, K., Hegde, S., & Murthy, S.. Energy efficient load sharing mechanism for multipath routing protocol in wireless sensor networks. In International Conference on Information Processing . Springer, Berlin, Heidelberg. pp. 422-427, August, 2011.
[6] Priya, M. M., & Kumari, A.. Traffic aware multipath communication for time-critical applications in underwater acoustic sensor networks. Int J Manag IT Eng, 2(7), 66-73, 2012.
[7] Kumar, V. N., Kumar, M. S., Rajakumari, J., & Mohanarangan, S.. Opportunistic void avoidance routing for underwater sensor networks. Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol, 2, 924-930, 2017.
[8] Patil, M. S. A., & Mishra, M. P.. Improved mobicast routing protocol to minimize energy consumption for underwater sensor networks. International Journal of Research In Science & Engineering, 3(2), 201, 2017.
[9] Gjanci, P., Petrioli, C., Basagni, S., Phillips, C. A., Bölöni, L., & Turgut, D.. Path finding for maximum value of information in multi-modal underwater wireless sensor networks. IEEE Transactions on Mobile Computing, 17(2), 404-418, 2017.
[10] Abbasi, J. S., Javaid, N., Gull, S., Islam, S., Imran, M., Hassan, N., & Nasr, K.. Balanced energy efficient rectangular routing protocol for underwater wireless sensor networks. In 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), pp. 1634-1640, June 2017. IEEE.
[11] Akbar, M., Javaid, N., Khan, A. H., Imran, M., Shoaib, M., & Vasilakos, A.. Efficient data gathering in 3D linear underwater wireless sensor networks using sink mobility. Sensors, 16(3), 404, 2016.
[12] Souiki, S., Hadjila, M., & Feham, M.. Fuzzy based clustering and energy efficient routing for underwater wireless sensor networks. International Journal of Computer Networks & Communications, 7(2), 33, 2015.