Volume 5 , Issue 1 , PP: 08-21, 2022 | Cite this article as | XML | Html | PDF
Heba M. Fadhil 1 * , Muna M. Hummady 2 , Noor Q. Makhool 3 , Zinah O. Dawood 4
Doi: https://doi.org/10.54216/IJWAC.050101
The development of wireless sensor networks (WSNs) in the underwater environment leads to underwater WSN (UWSN). It has severe impact over the research field due to its extensive and real-time applications. However effective execution of underwater WSNs undergoes several problems. The main concern in the UWSN is sensor nodes’ energy depletion issue. Energy saving and maintaining quality of service (QoS) becomes highly essential for UWASN because of necessity of QoS application and confined sensor nodes (SNs). To overcome this problem, numerous prevailing methods like adaptive data forwarding techniques, QoS-based congestion control approaches, and various methods have been devised with maximum throughput and minimum network lifespan. This study introduces a novel Seeker Optimization based Energy Aware Clustering Scheme for Underwater Wireless Sensor Networks (SOEACS-UWN). The presented SOEACS-UWN model follows the operation on a collection of solutions named search population (i.e., human team) and considered optimization procedure as a searching process of optimum solutions via human teams. The SOEACS-UWN model constructs a fitness function for effectual CH choices using diverse variables namely distance, residual energy, node degree, centrality, and link quality. The simulation analysis of the SOEACS-UWN model is tested and the outcomes were investigated under diverse aspects. The experimental outcomes demonstrated the supremacy of the SOEACS-UWN model over other approaches.
Underwater wireless sensor networks , Energy efficiency , Clustering , Object function , Seeker optimization
[1] Wan, Z., Liu, S., Ni, W. and Xu, Z., 2019. An energy-efficient multi-level adaptive clustering routing
algorithm for underwater wireless sensor networks. Cluster Computing, 22(6), pp.14651-14660.
[2] Xiao, X. and Huang, H., 2020. A clustering routing algorithm based on improved ant colony
optimization algorithms for underwater wireless sensor networks. Algorithms, 13(10), p.250.
[3] Subramani, N., Mohan, P., Alotaibi, Y., Alghamdi, S. and Khalaf, O.I., 2022. An efficient
metaheuristic-based clustering with routing protocol for underwater wireless sensor
networks. Sensors, 22(2), p.415.
[4] Mohan, P., Subramani, N., Alotaibi, Y., Alghamdi, S., Khalaf, O.I. and Ulaganathan, S., 2022.
Improved metaheuristics-based clustering with multihop routing protocol for underwater wireless
sensor networks. Sensors, 22(4), p.1618.
[5] Xiao, X., Chi, C., Huang, H., Huang, J. and Wang, W., 2020, October. An energy-efficient clustering
routing protocol based on data aggregation for underwater acoustic sensor networks. In Global Oceans
2020: Singapore–US Gulf Coast (pp. 1-6). IEEE.
[6] Anuradha, D., Subramani, N., Khalaf, O.I., Alotaibi, Y., Alghamdi, S. and Rajagopal, M., 2022.
Chaotic search-and-rescue-optimization-based multi-hop data transmission protocol for underwater
wireless sensor networks. Sensors, 22(8), p.2867.
[7] Xing, G., Chen, Y., Hou, R., Dong, M., Zeng, D., Luo, J. and Ma, M., 2021. Game-theory-based
clustering scheme for energy balancing in underwater acoustic sensor networks. IEEE Internet of
Things Journal, 8(11), pp.9005-9013.
[8] Karim, S., Shaikh, F.K., Aurangzeb, K., Chowdhry, B.S. and Alhussein, M., 2021. Anchor nodes
assisted cluster-based routing protocol for reliable data transfer in underwater wireless sensor
networks. IEEE Access, 9, pp.36730-36747.
[9] Ahmed, M., Salleh, M. and Channa, M.I., 2018. CBE2R: Clustered-based energy efficient routing
protocol for underwater wireless sensor network. International Journal of Electronics, 105(11),
pp.1916-1930.
[10] Bhattacharjya, K., Alam, S. and De, D., 2019. CUWSN: energy efficient routing protocol selection for
cluster based underwater wireless sensor network. Microsystem Technologies, pp.1-17.
[11] Xiao, X., Huang, H. and Wang, W., 2020. Underwater wireless sensor networks: An energy-efficient
clustering routing protocol based on data fusion and genetic algorithms. Applied Sciences, 11(1),
p.312.
[12] Gomathi, R.M., Manickam, J.M.L., Sivasangari, A. and Ajitha, P., 2020. Energy efficient dynamic
clustering routing protocol in underwater wireless sensor networks. International Journal of
Networking and Virtual Organisations, 22(4), pp.415-432
[13] Li, L., Qiu, Y. and Xu, J., 2022, April. A K-Means Clustered Routing Algorithm with Location and
Energy Awareness for Underwater Wireless Sensor Networks. In Photonics (Vol. 9, No. 5, p. 282).
MDPI.
[14] Chaaf, A., Saleh Ali Muthanna, M., Muthanna, A., Alhelaly, S., Elgendy, I.A., Iliyasu, A.M., El-Latif,
A. and Ahmed, A., 2021. Energy-efficient relay-based void hole prevention and repair in clustered
multi-AUV underwater wireless sensor network. Security and Communication Networks, 2021
[15] Chenthil, T.R. and Jayarin, P.J., 2022, March. Energy-Aware QoS Based Cluster Routing With
Aggregation Management Algorithm in Underwater Wireless Sensor Network. In 2022 International
Conference on Communication, Computing and Internet of Things (IC3IoT) (pp. 1-6). IEEE
[16] Lin, D. and Wang, Q., 2019. An energy-efficient clustering algorithm combined game theory and dualcluster-
head mechanism for WSNs. IEEE Access, 7, pp.49894-49905.
[17] Shafik, M.B., Chen, H., Rashed, G.I. and El-Sehiemy, R.A., 2019. Adaptive multi objective parallel
seeker optimization algorithm for incorporating TCSC devices into optimal power flow
framework. IEEE Access, 7, pp.36934-36947.
[18] Maheswari, M. and Karthika, R.A., 2021. A novel QoS based secure unequal clustering protocol with
intrusion detection system in wireless sensor networks. Wireless Personal Communications, 118(2),
pp.1535-1557.
