Towards the Development of Gaussian Clustering Algorithm Technology to Extend the Lifetime of MANETs

Mobile Ad hoc Networks (MANETs) are infrastructure-independent wireless networks where nodes communicate directly or through relays without a central base station. Routing protocols employed in MANETs face numerous challenges due to their limited resources. Cross-layer optimization is fundamental to conserving energy and achieving quality of service parameters. However, reducing end-to-end diversity conflicts with power consumption, creating a problem when trying to improve network lifetime. In this work, a Lifetime Enhancement Routing (LER) protocol, which selects the most efficient path to the destination using residual energy and cost exchange metrics, is proposed. LER primarily reduces node overutilization and load to prolong the network lifetime. The proposed MANET performance optimization technique is Gaussian clustering algorithm with one of the deep learning (RNN) techniques as a combined technique. The simulation results show that the proposed protocol significantly reduced energy consumption and augmented the ability to send data through the best path available in the network with a high efficiency of up to 92%.