Open Access

ARTICLE

Differential Evolution with Arithmetic Optimization Algorithm Enabled Multi-Hop Routing Protocol

Manar Ahmed Hamza^1,*, Haya Mesfer Alshahrani², Sami Dhahbi³, Mohamed K Nour⁴, Mesfer Al Duhayyim⁵, ElSayed M. Tag El Din⁶, Ishfaq Yaseen¹, Abdelwahed Motwakel¹

1 Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, AlKharj, Saudi Arabia
2 Department of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia
3 Department of Computer Science, College of Science & Art at Mahayil, King Khalid University, Abha, 62529, Saudi Arabia
4 Department of Computer Science, College of Computing and Information System, Umm Al-Qura University, Saudi Arabia
5 Department of Computer Science, College of Sciences and Humanities- Aflaj, Prince Sattam bin Abdulaziz University, Saudi Arabia
6 Department of Electrical Engineering, Faculty of Engineering and Technology, Future University in Egypt, New Cairo, 11845, Egypt

* Corresponding Author: Manar Ahmed Hamza. Email:

Computer Systems Science and Engineering 2023, 45(2), 1759-1773. https://doi.org/10.32604/csse.2023.030581

Received 29 March 2022; Accepted 09 June 2022; Issue published 03 November 2022

Abstract

Wireless Sensor Networks (WSN) has evolved into a key technology for ubiquitous living and the domain of interest has remained active in research owing to its extensive range of applications. In spite of this, it is challenging to design energy-efficient WSN. The routing approaches are leveraged to reduce the utilization of energy and prolonging the lifespan of network. In order to solve the restricted energy problem, it is essential to reduce the energy utilization of data, transmitted from the routing protocol and improve network development. In this background, the current study proposes a novel Differential Evolution with Arithmetic Optimization Algorithm Enabled Multi-hop Routing Protocol (DEAOA-MHRP) for WSN. The aim of the proposed DEAOA-MHRP model is select the optimal routes to reach the destination in WSN. To accomplish this, DEAOA-MHRP model initially integrates the concepts of Different Evolution (DE) and Arithmetic Optimization Algorithms (AOA) to improve convergence rate and solution quality. Besides, the inclusion of DE in traditional AOA helps in overcoming local optima problems. In addition, the proposed DEAOA-MRP technique derives a fitness function comprising two input variables such as residual energy and distance. In order to ensure the energy efficient performance of DEAOA-MHRP model, a detailed comparative study was conducted and the results established its superior performance over recent approaches.

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Keywords

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