Enhanced Energy Efficient Routing Protocol (EEE-RP) to forward the Data Packets and to improve QoS in Wireless Sensor Networks by Means of Machine Learning Methods

Abstract

Objectives: To propose an energy-efficient routing protocol for forwarding Data Packets for effective transmission of captured data using Machine Learning Methods in order to enhance WSN service efficiency. Methods: This study proposes a new routing mechanism Enhanced Energy Efficient Routing Protocol (EEE-RP) to extend the network life by reducing end-to-end delays by forwarding data packets to their destinations in the most efficient and optimal way possible using the best path. To forward data packets in a dynamic and noise-free manner, machine learning approaches such as reinforcement learning, random walk data collection, and Markov decision process framework methods are used. Findings: To demonstrate the efficiency of the proposed EEE-RP protocol, the NS2 Version 35 simulator is used. The simulation results are compared to the baseline EH-WSN and ECO-LEACH protocols in terms of data arrival rate, packet drop ratio, packet delivery ratio, energy consumption, network traffic, delay and network lifetime to show the superior performance in forwarding the data packets in an efficient manner. Novelty: According to the results of the comprehensive study, EEE-RP performs better at detecting network failures, selecting the most appropriate route to forward data packets, minimizing energy consumption, minimizing delay time, and enhancing the network lifetime. Keywords: Energy Efficient Protocol; Sensor Networks; Machine Learning;Packets; Routing