SPARTA-GEMSTONE: A two-phase approach for efficient node placement in 3D WSNs under Q-Coverage and Q-Connectivity constraints

Abstract

Wireless sensor networks (WSNs) face challenges in achieving robust target coverage and connectivity, particularly when varying priorities for targets are modeled with $Q$-Coverage and $Q$-Connectivity constraints. However, existing studies often neglect minimizing the number of nodes under these constraints in 3D environments or focus on sensor-to-sensor connections, which are less suitable for target-oriented networks. This paper bridges these gaps by proposing a novel two-phase heuristic approach. In Phase I, we introduce SPARTA, with two variants (SPARTA-CC and SPARTA-CP), to address $Q$-Coverage. Phase II employs GEMSTONE, a heuristic algorithm based on a minimum spanning tree, to ensure $Q$-Connectivity. Our method is evaluated on a real-world 3D dataset and compared against baseline methods. The results demonstrate that our approach significantly reduces the number of nodes while improving running speed. Our proposal can save 13% of the node count while running 2370 times faster than the current state-of-the-art method. These contributions advance the state of the art in WSN design and hold significant implications for efficient and fault-tolerant network deployment in practical scenarios.