Maximizing Wireless Sensor Networks Coverage and Connectivity in Irregular Terrains Using Grover’s Quantum Algorithm

The complicated topographical limitations and NP-hard nature of the sensor placement problem make it difficult to achieve optimal coverage and connectivity in wireless sensor networks (WSNs) deployed over irregular terrains. WSNs encounter critical challenges in uneven regions due to irregular obstacles, elevation variations, and dynamic terrain profiles, all of which influence coverage and connectivity. Classical methods, such as greedy or evolutionary strategies, often struggle to scale efficiently as terrain complexity increases and may converge to suboptimal solutions due to their heuristic nature. This article applies Grover’s quantum search algorithm to enhance sensor placement, the primary focus of this study. Unlike classical techniques that traverse solution spaces step by step, the Grover algorithm enhances the search process with a quadratic speedup. This enhancement enables the efficient identification of near-optimal sensor configurations in complicated contexts. This quantum-assisted method not only reduces the number of necessary sensors but also enhances performance in coverage and connectivity metrics, along with a substantial decrease in computation burden. The integration of terrain awareness and quantum search diverges significantly from traditional approaches, providing an intelligent, scalable, and computationally promising methodology for WSN deployment in the real-world terrains.