A Hybrid Trust Based WSN protocol to Enhance Network Performance using Fuzzy Enabled Machine Learning Technique

Authors

  • Lalit Kumar Tyagi Computer Science and Engineering, Banasthali Vidyapith, Tonk-Newai, Rajasthan, India
  • Anoop Kumar Computer Science and Engineering, Banasthali Vidyapith, Tonk-Newai, Rajasthan, India

Keywords:

Cluster, Fuzzy Logic, Cluster Head, Clustering, Sensor Node

Abstract

This paper proposes a trust-based cluster head selection method for Wireless Sensor Networks (WSNs) using machine learning. It utilizes historical behavior and performance data of sensor nodes to establish trustworthiness. Machine learning algorithms are employed to build a trust model during the training phase, considering features like energy levels and communication quality. Real-time cluster head selection is based on trust scores calculated using the trust model. Simulations demonstrate improved network reliability, energy efficiency, and data accuracy compared to traditional methods. The approach also shows resilience against attacks and node failures. Overall, this research contributes to enhancing WSN efficiency and security.

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Published

12.07.2023

How to Cite

Tyagi, L. K. ., & Kumar, A. . (2023). A Hybrid Trust Based WSN protocol to Enhance Network Performance using Fuzzy Enabled Machine Learning Technique. International Journal of Intelligent Systems and Applications in Engineering, 11(9s), 131–144. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3101

Issue

Vol. 11 No. 9s (2023)

Section

Research Article

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