Energy Efficient Wireless Sensor Networks Through PUMA Based Clustering and Grid Routing

Energy efficiency and prolonged network lifetime remain key challenges in wireless sensor networks. Clustering, cluster head selection, and routing are central to addressing these issues since they directly affect energy consumption, data delivery, and overall network stability. In this work, we introduce PUMA-GRID, a protocol that combines the Puma Optimization Algorithm for adaptive cluster head selection with a grid-based A* inspired multi hop routing scheme. The fitness function for cluster head election incorporates intra cluster distance, distance to the base station, and residual energy, with adjustable weights that allow flexible adaptation to deployment scenarios. Simulation experiments were performed under different base station placements and weight configurations to assess the influence of each factor. The results show that the effect of the weights depends strongly on base station location, and that careful tuning is required to balance efficiency and fairness. Across all scenarios, PUMA-GRID demonstrated superior performance compared to LEACH, AEO based schemes, and other PUMA variants. It achieved longer stability periods, higher packet delivery, lower overhead, more uniform coverage, and greater residual energy preservation. These outcomes confirm that the combination of PUMA optimization with grid based routing provides an effective and scalable solution for sustainable operation of wireless sensor networks.