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

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

Published on: September 8, 2023

Energy efficient traffic data aggregation and routing for metropolitan optical access network.

T Senthil Kumar¹, Mohan V², S Senthilkumar³

¹Department of Electronics and Communication Engineering, M.Kumarasamy College of Engineering, Karur, Tamilnadu, 639113, India. tskumar5585@gmail.com.

Scientific Reports

|October 1, 2025

Summary

This summary is machine-generated.

This study introduces an energy-efficient metropolitan optical access network (MOAN) using adaptive principal component analysis (APCA) for traffic grooming and adaptive Tuna Swarm Optimization (ATSSO) for routing. The approach significantly reduces energy consumption and improves network performance.

Keywords:

Dynamic wavelength allocation Energy efficient routing Metropolitan optical access network Traffic data aggregation

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Area of Science:

Optical Networking
Energy Efficiency in Telecommunications
Metropolitan Area Networks

Background:

Increasing demand for high-speed data transmission in metropolitan areas necessitates energy-efficient solutions.
Existing optical networks face challenges in optimizing energy consumption and network lifetime.
Metropolitan Optical Access Networks (MOAN) require advanced strategies for efficient resource utilization and power management.

Purpose of the Study:

To develop and evaluate an energy-efficient traffic data aggregation and routing strategy for Metropolitan Optical Access Networks (MOAN).
To enhance network lifetime and optimize resource utilization through intelligent data grooming and path selection.
To reduce energy consumption while maintaining high data throughput and low packet delay.

Main Methods:

Wavelength utility-based dynamic wavelength allocation (WU-DWA) for efficient resource utilization.
Adaptive Principal Component Analysis (APCA) for traffic grooming and data aggregation.
Energy-efficient adaptive Tuna Swarm Optimization (ATSSO) strategy for energy-aware routing.

Main Results:

Achieved an energy consumption of 88 units.
Obtained a throughput of 131.63 units.
Reduced average packet delay to 3.551 units.
Reported energy savings of 29.99%.

Conclusions:

The proposed energy-efficient approach significantly outperforms traditional methods in Metropolitan Optical Access Networks (MOAN).
The integration of APCA for traffic grooming and ATSSO for routing enhances network lifetime and efficiency.
The study demonstrates a viable solution for high-speed, energy-conscious data transmission in metropolitan environments.