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

Abstract

<span>A wireless sensor network (WSN) composed by a large number of sensor nodes that are insufficient in terms of processing power, storage and energy. The principal tasks of nodes is gathering and transmitting data collected to the base station (BS). Consequently the major essential criteria for designing a WSN are the network lifetime. In this paper an efficient GAF routing protocol for gathered data is introduced. It proposes an energy-efficient routing in WSN based on the basic version. 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 using an optimized weighted sum model where maximum remaining energy and minimum distance criteria are considered. Moreover routing data is based on transmission range for enhancing the energy efficiency during data routing. The experimental results shows that the proposed EE-GAF produces better performance than the existing GAF basic and optimized-GAF routing protocol in terms of number of dead node and energy consumption. It is obviously proves that the proposed EE-GAF can improve the network lifetime</span>

Enhanced GAF protocol based on graph theory to optimize energy efficiency and lifetime in WSN technology

“…Nonetheless, in the proposed protocol (E-GAF), the sequence of active nodes is selected based on the higher residual energy and the Enhanced GAF in WSN lower distance from the BS, which overall improves the energy efficiency of the network. E-GAF has reduced energy consumption because it uses a new principle of transit of GAF states where the discovery phase is performed only once (Aznaoui et al, 2021b). In addition, modifying the selection criteria in our proposed protocol allowed us to control the selection of a single active node in each grid during data routing.…”

“…In fact, many sensors network protocols have been developed in recent years. Previous work in the areas of data collection (Qi and Qiu, 2009; Grover et al , 2014b; Kaur and Gujral, 2016; Aznaoui et al , 2021a, b) encourages us to develop an effective approach for large-scale sensor networks. Based on the minimum routing cost trees regenerated by our E-GAF version based on graph theory, the optimal message transmission path was selected, which reflects the significant importance of this step in optimizing the consumption of energy in a WSN (Aznaoui et al , 2019).…”

“…Wireless sensor network (WSN) routing protocols can be divided into flat-based protocols, hierarchy-based protocols and location-based protocols (Aznaoui et al , 2015). This section presents previous work-related of the location-based routing protocol for optimizing energy efficiency in WSNs (Aznaoui et al , 2018; Aziz and Aznaoui, 2020). Sensor nodes using routing protocols based on location type1 are identified by their geographic positions.…”

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