Design and Analysis of Enhanced LEACH based Energy Routing Protocol for Wireless Sensor Network

Abstract

In recent times, wireless sensor networks, or WSNs, have attracted a lot of attention because of their extensive use in a variety of fields, such as industrial automation, healthcare, and environmental monitoring. Energy efficiency is a major problem for WSNs since sensor nodes frequently run on batteries and have little energy available. Effective routing techniques are essential for extending the life of the network and guaranteeing dependable data transfer. This work focuses on the performance analysis and numerical modeling of a new routing strategy that combines machine learning approaches to improve WSN energy efficiency. The suggested routing algorithm optimizes energy consumption and overall network performance by adjusting its recommendations in real-time in response to environmental and network variables. We assess this machine learning-based routing protocol's performance using large-scale numerical simulations, contrasting it with conventional routing protocols and emphasizing its possible advantages in terms of energy efficiency and dependable data delivery. We investigate a variety of situations in our simulations, taking into account different network topologies, traffic patterns, and environmental factors. We evaluate many measures, including energy consumption, network lifetime, packet delivery ratio, and end-to-end delay, in order to offer a thorough evaluation of the efficacy of the machine learning-based routing protocol. The outcomes show how energy-efficient the protocol is, guaranteeing long-lasting sensor nodes and reliable data transfer while adjusting to changing network conditions.The results of this study highlight how machine learning approaches can completely change how routing protocols are designed and optimized in wireless sensor networks with limited energy. This research helps to construct sustainable and dependable WSNs by enhancing energy efficiency and network performance, which makes it easier to deploy sensor networks in crucial applications.