Oukas, NourredineBoulif, Menouar2023-03-142023-03-1420232193567Xhttps://link.springer.com/article/10.1007/s13369-022-06970-8DOI 10.1007/s13369-022-06970-8https://dspace.univ-boumerdes.dz/handle/123456789/11195In this paper, we propose a generalized stochastic Petri net (GSPN) to model the sensor node (SN) interaction in solar energy harvesting wireless sensor networks. Our GSPN formulation models the energy stored in the SN battery by using the quantization principle. Furthermore, it considers that the sensors’ deployment territory is subject to different sunshine levels. In addition, each SN adopts the double sleeping strategy to cope with solar energy shortage in the nighttime. We conduct a comparative analysis between the proposed model and three others taken from the literature to identify which is best suited to predicting the input parameters that extend the network lifetime to fulfill its long-lasting duty with decent performancesenDuty cycleGSPN modelingQuantizationSolar energy harvestingWireless sensor networksArticle