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.
Background: Enhancing quality of service in forwarding the data packets from source to destination in WSN is a major task in contemporary networks. Everywhere the usage of WSN is increasing in the real world. Data sensing, data capturing and data forwarding is a routine process in modern era. Some of the dynamic problems arise as link failure, routing issues, packet delay etc that lead to the entire network shutdown. Hence, there is a need for development or enhancement of the protocol that finds the finest route to forward data packets in an optimal way. Objectives: The main objective of this study is to propose a unified energy efficient protocol to minimize the delay which will result in successful delivery of data packets from source to destination to improve the quality of service in WSN. Methods: This study proposes Unified Energy Efficient Distributed Network Management Protocol (UEEDNMP) focuses mainly on forwarding the data packets and finite routing to minimize the end to end delay. Parametric search technique along with CAFSM method is utilized to design the proposed protocol, to meet out the objective by forwarding the packets with better path from source to destination. Findings: NS2 Version 35 simulator is used to calculate the performance of the proposed UEEDNMP protocol. The simulation result shows UEEDNMP outperforms the existing protocols EH-WSN and ECO-LEACH in terms of data arrival rate, packet drop ratio, packet delivery ratio, energy consumption, network traffic, delay and network lifetime. Novelty: Comprehensive analyses signify that UEEDNMP has greater performance in forwarding the data packets with the finest routing in distributed networks, minimizing energy consumption, minimize the end to end latency time and maximize the life span of the network.
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