Implementation and Performance Evaluation of Quantum-Inspired Clustering Scheme for Energy-Efficient WSNs.

Advancements in communication technologies and the proliferation of smart devices have significantly increased the demand for wireless sensor networks (WSNs). These networks play an important role in the IoT environment. The wireless sensor network has many sensor nodes that are used to monitor the surrounding environment. Energy consumption is the main issue in WSN due to the difficulty in recharging or replacing batteries in the sensor nodes. Cluster head selection is one of the most effective approaches to reduce overall network energy consumption. In recent years, quantum technology has become a growing research area. Various quantum-based algorithms have been developed by researchers for clustering. This article introduces a novel, energy-efficient clustering scheme called the quantum-inspired clustering scheme (QICS), which is based on the Quantum Grover algorithm. It is mainly used to improve the performance of cluster head selection in a wireless sensor network. The research conducted simulations that compared the proposed cluster selection method against established algorithms, LEACH, GSACP, and EDS-KHO. The simulation environment used 100 nodes connected via specific energy and communication settings. QICS stands out as the superior clustering method since it extends the lifetime of the network by 30.5%, decreases energy usage by 22.4%, and increases the packet delivery ratios by 19.8%. The quantum method achieved an increase in speed with its clustering procedure. This study proves how quantum-inspired techniques have become an emerging approach to handling WSN energy restrictions, thus indicating future potential for IoT systems with energy awareness and scalability.