Open Access

ARTICLE

Energy-Efficient Routing Protocol with Multi-Hop Fuzzy Logic for Wireless Networks

J. Gobinath^1,*, S. Hemajothi², J. S. Leena Jasmine³

1 Department of Information and Communication Engineering, Anna University, Chennai, 600025, India
2 Department of Electronics and Communication Engineering, Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai, 600062, India
3 Department of Computer Science and Engineering, Velammal Engineering College, Chennai, 600066, India

* Corresponding Author: J. Gobinath. Email:

Intelligent Automation & Soft Computing 2023, 36(2), 2457-2471. https://doi.org/10.32604/iasc.2023.031171

Received 12 April 2022; Accepted 08 June 2022; Issue published 05 January 2023

Abstract

A Wireless Sensor Network (WSN) becomes a newer type of real-time embedded device that can be utilized for a wide range of applications that make regular networking which appears impracticable. Concerning the energy production of the nodes, WSN has major issues that may influence the stability of the system. As a result, constructing WSN requires devising protocols and standards that make the most use of constrained capacity, especially the energy resources. WSN faces some issues with increased power utilization and an on going development due to the uneven energy usage between the nodes. Clustering has proven to be a more effective strategy in this series. In the proposed work, a hybrid method is used for reducing the energy consumption among CHs. A Fuzzy Logic-based clustering protocol FLUC (unequally clustered) and Fuzzy Clustering with Energy-Efficient Routing Protocol (FCERP) are used. A Fuzzy Clustering with Energy Efficient Routing Protocol (FCERP) reduces the WSN power usage and increases the lifespan of the network. FCERP has created a novel cluster-based fuzzy routing mechanism that uses a limit value to combine the clustering and multi-hop routing capabilities. The technique creates uneven groups by using fuzzy logic with a competitive range to choose the Cluster Head (CH). The input variables include the distance of the nodes from the ground station, concentrations, and remaining energy. The proposed FLUC-FCERP reduces the power usage and improves the lifetime of the network compared with the existing algorithms.

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Keywords

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