A Quantum-Based Energy-Efficient Clustering In Wireless Sensor Networks Using Grover’s Algorithm

Abstract

The demand for wireless sensor networks (wsns) has grown a lot because of improvements in technologies like communication and the rise of smart devices. These networks are very important in the iot world. There are a lot of sensor nodes in wireless sensor network that keep an eye on the area around them. The main problem with WSN is that it's hard to recharge or change the batteries in the sensor nodes, which makes energy use a big issue. Choosing a cluster head can be one of the best ways to cut down on amount of energy the whole network uses. Quantum technology has become a more popular area of research in the last few years. Researchers have created different quantum-based algorithms to do clustering. This research article presents an innovative, energy-efficient clustering methodology known as the quantum-based clustering scheme (QBCS), derived from the Quantum Grover algorithm. Its main purpose in wireless sensor network work to select the cluster head selection better. The study used simulations to compare with researcher work cluster selection method to well-known algorithms like EDS-KHO,IKM-EPSO and MSSA-DSSA-KMEANS. The simulation environment had 100 nodes that were linked together in a certain way for energy and communication. QBCS is the best clustering method because it makes the network last 30.5% longer, uses 22.4% less energy, and delivers packets 19.8% more often. The quantum method's clustering process made it faster.  This study demonstrates that quantum-inspired techniques have emerged as a novel approach to addressing energy constraints in wireless sensor networks (wsns), suggesting future possibilities for energy-aware and scalable Internet of Things (iot) systems.