Energy-Balanced Hierarchical Routing for Monitoring and Industrial IoT Applications in Dense Wireless Sensor Networks

The quick growth of large-scale Internet of Things (IoT) deployments has made it even more important for high-density wireless sensor networks (WSNs) to have stable and energy-efficient routing mechanisms. Traditional hierarchical routing protocols use linear, probability-based methods to choose cluster heads (CHs). These methods often cause random energy imbalance and early network fragmentation. This paper suggests an Advanced Quantum-Adaptive Hierarchical Routing (A-QAHR) protocol that uses a quantum-inspired stochastic tunneling (QST) mechanism for non-linear CH selection to get around these issues. The proposed model sees the energy left in a node as a dynamic state variable and uses quantum barrier logic to move CH duties away from nodes that need energy. A new cross-layer entanglement factor considers residual energy, node density, and distance to the sink to make sure that energy is used up evenly and routing is more stable. The proposed protocol was evaluated using Monte Carlo simulations implemented in MATLAB R2021a and comparing its results to those of state-of-the-art protocols like LEACH, SEP, and DEEC. The simulation results show that A-QAHR increases the stability period (the first node to die) by 30.5% compared to DEEC and by 67.7% compared to LEACH. The proposed protocol also lowers the average energy use per packet to 1.95 mJ and raises the total amount of data sent to the base station by 40.6%. A statistical analysis shows that the improvements are statistically significant (p < 0.005). Finally, A-QAHR protocol is a scalable and energy-balanced routing solution that is perfect for next-generation massive IoT applications that need a long network lifetime and high reliability.