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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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A Dynamic Trust evaluation and update model using advance decision tree for underwater Wireless Sensor Networks.

Sabir Shah¹, Asim Munir¹, Abdu Salam²

¹Department of Computer Science and Software Engineering, International Islamic University, Islamabad, 44000, Pakistan.

Scientific Reports

|September 27, 2024

Summary

This study introduces a dynamic trust model for underwater wireless sensor networks (UWSNs) using a modified decision tree. The model enhances security and efficiency in dynamic underwater environments.

Keywords:

Dynamic Modified decision tree Trust Underwater wireless sensor network

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Area of Science:

Computer Science
Network Engineering
Marine Technology

Background:

Underwater wireless sensor networks (UWSNs) face significant challenges like security, mobility, limited bandwidth, and high error rates.
Traditional trust models are inadequate for the dynamic and harsh underwater environment.
Existing methods often use static trust evaluations, failing to adapt to real-time conditions.

Purpose of the Study:

To propose a novel dynamic trust evaluation and update model specifically designed for UWSNs.
To address the limitations of traditional trust models in underwater environments.
To improve the security, accuracy, and operational efficiency of UWSNs.

Main Methods:

Development of a dynamic trust evaluation and update model utilizing a modified decision tree algorithm.
Incorporation of energy-aware decision-making and real-time adaptation to environmental factors.
Integration of underwater-specific parameters such as water currents and acoustic signal properties.

Main Results:

Achieved 96% accuracy in trust evaluation with a 2% false positive rate.
Demonstrated a 50 mW improvement in energy efficiency compared to baseline models.
Reduced response time to 20 ms per packet, enhancing operational speed.

Conclusions:

The proposed dynamic trust model effectively addresses UWSN challenges, enhancing security and operational efficiency.
Modified decision tree algorithms show significant potential for improving UWSN performance and sustainability.
The model's innovations offer a more robust and adaptive solution for underwater network trust management.