The Journal of Science and Engineering Applications (JSEA)

Abstract

Wireless Sensor Networks (WSNs) are collections of small, low-value nodes prepared with 
sensors, processor, transceiver, and power gadgets that may set up wi-fi communication. One of the 
primary demanding situations in WSNs is electricity intake. Clustering is an powerful method for 
reducing strength intake in wireless sensor networks with the aid of grouping nodes into clusters and 
choosing a subset of nodes as cluster heads liable for records aggregation and transmission.  
In this research, an energy-inexperienced clustering technique is proposed for wireless sensor 
networks the usage of an optimization set of regulations to cope with the electricity consumption 
hassle. The proposed approach makes use of the Arithmetic Optimization Algorithm (AOA) to 
optimize the clustering approach and reduce power intake. The set of rules starts via randomly 
assigning nodes to clusters and iteratively improves the answer via mathematics operators together 
with addition, subtraction, multiplication, and department.  
The efficiency of the solution is evaluated based on the fitness function which considers the 
energy consumption of each node and the distance between nodes. Experimental results show that the 
proposed method outperforms the existing clustering algorithms in terms of energy efficiency, and 
maintains high network availability and connectivity The proposed method has the potential to be 
controlled role in applications in WSNs where energy efficiency is an important factor.