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Energy-efficient data routing using neuro-fuzzy based data routing mechanism for IoT-enabled WSNs.

Sakthi Shunmuga Sundaram Paulraj¹, T Deepa²

¹Department of Electronics and Communication Engineering, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, 603203, India. sp8941@srmist.edu.in.

Scientific Reports

|December 3, 2024

Summary

This study introduces a Neuro-fuzzy-based Data Routing (NFDR) mechanism for efficient data routing and cluster formation in Internet of Things (IoT) Wireless Sensor Networks (WSNs). NFDR improves network performance by enhancing energy retention and reducing delay and dead nodes.

Keywords:

And network efficiency Dynamic environment adaptability IoT-enabled WSNs Maximum data transmission rate Neuro-fuzzy based data routing Scalability feature

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Area of Science:

Computer Science
Electrical Engineering
Network Engineering

Background:

Internet of Things (IoT) enabled Wireless Sensor Networks (WSNs) face challenges in efficient data routing and dynamic cluster formation.
Existing mechanisms often struggle with scalability and maintaining network parameter thresholds.

Purpose of the Study:

To propose a novel Neuro-fuzzy-based Data Routing (NFDR) mechanism for enhanced data routing and cluster formation in IoT-enabled WSNs.
To improve network efficiency, energy retention, and reduce end-to-end delay and node mortality.

Main Methods:

The NFDR mechanism utilizes a neural network for cluster formation requirements and fuzzy logic for objective function adjustment.
Optimal scalability factors are computed from historical and current network parameters to sustain nodes within clusters.
A dynamic cluster formation approach with super head selection and adjusted cluster member size is employed.

Main Results:

The NFDR mechanism demonstrated enhanced clustering range and an increased number of cluster members.
Simulation results showed 75% energy retention, a 20% reduction in end-to-end delay, and a 15% decrease in dead nodes.
The proposed mechanism effectively sustains network parameter thresholds during data transmission.

Conclusions:

The Neuro-fuzzy-based Data Routing (NFDR) mechanism offers an efficient and robust solution for IoT-enabled WSNs.
NFDR significantly improves key performance metrics, contributing to more reliable and sustainable WSN operations.
This approach provides a foundation for developing advanced routing strategies in resource-constrained IoT environments.