Walrus Optimizer Based Novel Energy-Efficient Clustering for Wireless Sensor Network

Hind E. Mohammed; Lamyaa Hasan  Yousif; Shaimaa Kareem  Abdallah

Hind E. Mohammed Office Reconstruction and Projects, Ministry of Higher Education and Scientific Research, Baghdad, Iraq
Lamyaa Hasan Yousif Office Reconstruction and Projects, Ministry of Higher Education and Scientific Research, Baghdad, Iraq
Shaimaa Kareem Abdallah Department of Mathematics, College of Education for Pure Sciences, Al-Muthanna University, Al-Muthanna, Iraq

Keywords: Walrus Optimizer, Wireless Sensor Networks, Energy Efficiency, Clustering, Optimization Algorithms

Abstract

Wireless sensor networks (WSNs) have important role in modern Internet of Things (IoT) systems also make effective set of data as well as transmitting able. Although, energy sources restrictions in sensor nodes refers to basic concern, particularly in big-scale networks. Techniques based on clustering were presented as efficient concern for raising effectiveness of energy, however optimum clusters’ shape is yet the essential study concern. In this paper, the new mechanism of clustering given the Walrus Optimizer algorithm is defined. Such algorithm, inspired by group walruses manner, optimizes formation and head selection cluster with decreasing energy use and balanced load share objective between nodes. Outcomes of simulation illustrate that presented technique given the Walrus Optimizer performs better than traditional algorithms like Genetic Algorithms (GA) also Particle Swarm Optimization (PSO) in case of network life and energy effectiveness. Specifically, the technique develops network lifetime by 13.45% and decreases use of energy by 10-15% in comparison with base techniques. Present study results illustrate Walrus Optimizer algorithm ability to solve main WSNs issues and paves the way for later study in applying nature-inspired mechanisms’ domain in WSNs.

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