QIRA: A Quantum-Inspired Cluster Head Selection Algorithm for Wireless Sensor Networks

Cluster Head Selection (CHS) is one of the critical tasks in Wireless Sensor Networks (WSNs) as it directly impacts the network's performance and lifetime. In this manuscript, a Quantum-Inspired Recommendation Algorithm (QIRA) for optimal cluster head selection in WSNs has been proposed. QIRA utilizes the superposition and entanglement properties of quantum mechanics to explore the search space of potential cluster head candidates. The algorithm is designed to consider multiple features such as residual energy, distance to the base station, and node centrality during the process of Cluster Head Selection. The evaluation of the proposed QIRA algorithm, is has been done using wide-ranging simulations and compared with existing cluster head selection processes. The results demonstrate that QIRA is able to achieve significant improvements in terms of network lifetime, energy consumption, and data throughput.