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Coyote Optimization Using Fuzzy System for Energy Efficiency in WSN

Ahmed S. Almasoud1, Taiseer Abdalla Elfadil Eisa2, Marwa Obayya3, Abdelzahir Abdelmaboud4, Mesfer Al Duhayyim5, Ishfaq Yaseen6, Manar Ahmed Hamza6,*, Abdelwahed Motwakel6

1 Department of Information Systems, College of Computer and Information Sciences, Prince Sultan University,Saudi Arabia
2 Department of Information Systems-Girls Section, King Khalid University, Mahayil, 62529, Saudi Arabia
3 Department of Biomedical Engineering, College of Engineering, Princess Nourah Bint Abdulrahman University, Riyadh, 11671, Saudi Arabia
4 Department of Information Systems, College of Science and Artsat Mahayil, King Khalid University, Saudi Arabia
5 Department of Natural and Applied Sciences, College of Community-Aflaj, Prince Sattam bin Abdulaziz University, Saudi Arabia
6 Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, AlKharj, Saudi Arabia

* Corresponding Author: Manar Ahmed Hamza. Email: email

Computers, Materials & Continua 2022, 72(2), 3269-3281.


In recent days, internet of things is widely implemented in Wireless Sensor Network (WSN). It comprises of sensor hubs associated together through the WSNs. The WSN is generally affected by the power in battery due to the linked sensor nodes. In order to extend the lifespan of WSN, clustering techniques are used for the improvement of energy consumption. Clustering methods divide the nodes in WSN and form a cluster. Moreover, it consists of unique Cluster Head (CH) in each cluster. In the existing system, Soft-K means clustering techniques are used in energy consumption in WSN. The soft-k means algorithm does not work with the large –scale wireless sensor networks, therefore it causes reliability and energy consumption problems. To overcome this, the proposed Load-Balanced Clustering conjunction with Coyote Optimization with Fuzzy Logic (LBC-COFL) algorithm is used. The main objective is to perform the lifespan by balancing the gateways with the load of less energy. The proposed algorithm is evaluated using the metrics such as energy consumption, throughput, central tendency, network lifespan, and total energy utilization.


Cite This Article

APA Style
Almasoud, A.S., Eisa, T.A.E., Obayya, M., Abdelmaboud, A., Duhayyim, M.A. et al. (2022). Coyote optimization using fuzzy system for energy efficiency in WSN. Computers, Materials & Continua, 72(2), 3269-3281.
Vancouver Style
Almasoud AS, Eisa TAE, Obayya M, Abdelmaboud A, Duhayyim MA, Yaseen I, et al. Coyote optimization using fuzzy system for energy efficiency in WSN. Comput Mater Contin. 2022;72(2):3269-3281
IEEE Style
A.S. Almasoud et al., "Coyote Optimization Using Fuzzy System for Energy Efficiency in WSN," Comput. Mater. Contin., vol. 72, no. 2, pp. 3269-3281. 2022.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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