Sparrow-based Differential Evolutionary Search Algorithm for Mobility Aware Energy Efficient Clustering in MANET Network

Authors

  • Gunjan Bhatnagar Assistant Professor, School of Engineering and Computer, Dev Bhoomi Uttarakhand University, Uttarakhand, India
  • Gobi N. Assistant Professor, Department of Computer Science and IT, Jain(Deemed-to-be University), Bangalore-27, India
  • Humera Aqeel Assistant Professor, College of Computing Science and Information Technology, Teerthanker Mahaveer University, Moradabad, Uttar Pradesh, India
  • Brijraj Singh Solanki Assistant professor, School of Computer Science & System, JAIPUR NAITONAL UNIVERSITY, JAIPUR, India

Keywords:

MANET, cluster head (CH), sparrow-based differential evolutionary search algorithm (SDESA), LEACH

Abstract

A mobile node network that self-organizes and lacks a fixed infrastructure is called a mobile ad hoc network (MANET). If not effectively managed, the dynamic topology feature of MANETs can reduce network performance, mobility awareness, and energy efficiency, especially with regard to cluster head (CH) selection. The Low Energy Adaptive Clustering Hierarchy (LEACH) protocol is frequently used in MANETs to extend network lifetime by effectively utilizing the minimal energy provided. In this research, we present the Sparrow-based Differential Evolutionary Search Algorithm (SDESA) to solve the problem of energy efficiency in the communication process by selecting cluster heads. The suggested technique enhances network lifetime by combining the dynamic ability of differential evolution with the high degree of search effectiveness of the Sparrow Search technique. By integrating differential evolution's dynamic abilities with the high degree of search effectiveness of the recommended technique, node lifetime is increased.

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Published

11.07.2023

How to Cite

Bhatnagar, G. ., N., G. ., Aqeel, H. ., & Solanki, B. S. . (2023). Sparrow-based Differential Evolutionary Search Algorithm for Mobility Aware Energy Efficient Clustering in MANET Network. International Journal of Intelligent Systems and Applications in Engineering, 11(8s), 135–142. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3032

Issue

Vol. 11 No. 8s (2023): Advances on Machine Learning and Artificial Intelligence in Computer Technology

Section

Research Article

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