An efficient GAF routing protocol using an optimized weighted sum model in WSN

A wireless sensor network (WSN) is composed of a large number of sensor nodes that are insufficient in terms of processing power, storage, and energy. The principal tasks of nodes are gathering and transmitting data collected to the base station (BS). Consequently, the essential criteria for designing a WSN are the network lifetime. In this paper, we proposed an efficient geographic adaptative fidelity (GAF) routing protocol for gathering data. In this system, sensor nodes are distributed using Gaussian law, and an active leader is elected for each virtual grid to reduce the energy dissipated. An optimized weighted sum model is used to resolve this problem, where the maximum remaining energy and minimum distance criteria are considered as essential criteria. Moreover, routing data focuses on the transmission range for enhancing energy efficiency. The experimental results show that the proposed energyefficient GAF produces better performance than the existing, GAF basic and optimized-GAF routing protocol in terms of the number of dead nodes and energy consumption. It is obviously proved that the proposed efficient GAF can improve the network's lifetime.