A Two-Stage Approach for Secure Node Localization and Optimal Route Selection for Enhanced Performance in Wireless Sensor Networks

In Wireless Sensor Network (WSN), node localization is a crucial need for precise data gathering and effective communication. However, high energy requirements, long inter-node distances and unpredictable limitations create problems for traditional localization techniques. This study proposes an innovative two-stage approach to improve localization accuracy and maximize route selection in WSNs. In the first stage, the Self-Adaptive Binary Waterwheel Plant Optimization (SA-BWP) algorithm is used to evaluate a node’s trustworthiness to achieve accurate localization. In the second stage, the Gazelle-Enhanced Binary Waterwheel Plant Optimization (G-BWP) method is employed to determine the most effective data transfer path between sensor nodes and the sink. To create effective routes, the G-BWP algorithm takes into account variables like energy consumption, shortest distance, delay and trust. The goal of the proposed approach is to optimize WSN performance through precise localization and effective routing. MATLAB is used for both implementation and evaluation of the model, which shows improved performance over current methods in terms of throughput, delivery ratio, network lifetime, energy efficiency, delay reduction and localization accuracy in terms of various number of nodes and rounds. The proposed model achieves highest delivery ratio of 0.97, less delay of 5.39, less energy of 23.3 across various nodes and rounds.

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Publication Details

Journal
Journal of Circuits Systems and Computers
Published
2024-10-17
DOI
https://doi.org/10.1142/s0218126625501221
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
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article

A Two-Stage Approach for Secure Node Localization and Optimal Route Selection for Enhanced Performance in Wireless Sensor Networks

D. Ramesh, T. P. Mohan Kumar
Journal of Circuits Systems and Computers
Energy Efficient Wireless Sensor Networks
article

A Two-Stage Approach for Secure Node Localization and Optimal Route Selection for Enhanced Performance in Wireless Sensor Networks

D. Ramesh, T. P. Mohan Kumar
article en

Abstract

In Wireless Sensor Network (WSN), node localization is a crucial need for precise data gathering and effective communication. However, high energy requirements, long inter-node distances and unpredictable limitations create problems for traditional localization techniques. This study proposes an innovative two-stage approach to improve localization accuracy and maximize route selection in WSNs. In the first stage, the Self-Adaptive Binary Waterwheel Plant Optimization (SA-BWP) algorithm is used to evaluate a node’s trustworthiness to achieve accurate localization. In the second stage, the Gazelle-Enhanced Binary Waterwheel Plant Optimization (G-BWP) method is employed to determine the most effective data transfer path between sensor nodes and the sink. To create effective routes, the G-BWP algorithm takes into account variables like energy consumption, shortest distance, delay and trust. The goal of the proposed approach is to optimize WSN performance through precise localization and effective routing. MATLAB is used for both implementation and evaluation of the model, which shows improved performance over current methods in terms of throughput, delivery ratio, network lifetime, energy efficiency, delay reduction and localization accuracy in terms of various number of nodes and rounds. The proposed model achieves highest delivery ratio of 0.97, less delay of 5.39, less energy of 23.3 across various nodes and rounds.

Journal of Circuits Systems and ComputersVol. 34(05)
Sri Siddhartha Medical College (IN)
Affordable and clean energy
Openalex Percentile: Top 80%
Energy Efficient Wireless Sensor Networks
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A Two-Stage Approach for Secure Node Localization and Optimal Route Selection for Enhanced Performance in Wireless Sensor Networks — D. Ramesh, T. P. Mohan Kumar · Journal of Circuits Systems and Computers (2024) | TGRS Research Map | TGRS