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Modified Optimization for Efficient Cluster-based Routing Protocol in Wireless Sensor Network

Marwah Mohammad Almasri1,*, Abrar Mohammed Alajlan2

1 College of Computing and Informatics, Saudi Electronic University, Riyadh, 93499, KSA
2 Self-Development Skills Department, Common First Year Deanship, King Saud University, Riyadh, 11451, KSA

* Corresponding Author: Marwah Mohammad Almasri. Email: email

Intelligent Automation & Soft Computing 2022, 33(3), 1687-1710.


Wireless Sensor Networks (WSN) comprise numerous sensor nodes for monitoring specific areas. Great deals of efforts have been achieved to obtain effective routing approaches using clustering methods. Clustering is considered an effective way to provide a better route for transmitting the data, but cluster head selection and route generation is considered as a complicated task. To manage such complex issues and to enhance network lifetime and energy consumption, an energy-effective cluster-based routing approach is proposed. As the major intention of this paper is to select an optimal cluster head, this paper proposes a modified golden eagle optimization (M-GEO) algorithm to figure out the most significant issue of choosing an optimal cluster head in every cluster. The M-GEO algorithm selects an optimal cluster head among all the sensors by employing diverse factors namely the residual energy, node degree, distance among the nearby sensors, centrality of sensor nodes as well as distance between the cluster head and sink node. Additionally, the yellow saddle goatfish (YSG) optimization algorithm is employed in generatingan optimal routing path from the cluster head to the base station. Also, the YSG optimization algorithm detectsthe shortest routing path thereby minimizing the energy consumption. Then later, the performance analyses for various parameters are performed to evaluate the performance of the proposed approach.


Cite This Article

M. Mohammad Almasri and A. Mohammed Alajlan, "Modified optimization for efficient cluster-based routing protocol in wireless sensor network," Intelligent Automation & Soft Computing, vol. 33, no.3, pp. 1687–1710, 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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