Network life time augmentation of WSN through efficient energy using GAN algorithm

Abstract

The minimal energy sensor nodes are critical to the long-term viability of any wireless sensor network WSN). Clustering is used for this purpose. Choosing an efficient Cluster Head (CH) is critical in such cluster-based networks, as they are accountable for aggregating and transmitting data from their associate nodes to the base station (BS). A Generative Adversarial Networks (GAN) is proposed in this work to improve the selection of CH. As part of the fitness function, nodes’ residual energy, average energy, and inter-cluster distance are all considered. In an effort to further reduce energy consumption, a GAN routing method is proposed for use at the base station level for Efficient Energy. Simulations are used to evaluate the proposed ideal.The WSNs which require long life time with minimum cost sensors demand the proposed work. The research about the human unattainable places can be fit to necessitate this work. This method supports the maintenance of mines and petroleum refineries. In terms of energy consumption and network life expectancy, the results demonstrate a substantial improvement. And also, the proposed technique is analyzed and compared along with the existing approaches as Low-Energy Adaptive Clustering Hierarchy (Security based (S-LEACH), Cluster based (C-LEACH, More Energy Efficient-LEACH) (ME-LEACH) schemes. The proposed method detects the best location of storage-nodes for the sensor network. There is no need of agitation on battery drain up of storage-nodes (because of wireless recharge) which is a highly energy spending unit. The proposed method improves the network lifetime by a significant level. The proposed method is best fit to mines, petroleum refineries, forest department and military. The proposed method behaves as not only better storage scheme but also best fit to retrieval schemes.