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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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An efficient multi-objective framework for wireless sensor network using machine learning.

Sunil Kumar Gupta1, Vivek Kumar Pandey2, Idrees Alsolbi3

  • 1Sant Gahira Guru Vishwavidyalaya, Sarguja, Ambikapur, Chhattisgarh, India.

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|February 21, 2025
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Summary
This summary is machine-generated.

A new model enhances wireless sensor networks (WSNs) for Internet of Things (IoT) efficiency. Tested on 25 benchmark problems, it offers a superior solution for complex IoT networks.

Keywords:
Bench-mark IOT problems evolutionary algorithm (EA)High-performance computing (HPC)Internet of things (IoT)Multi-objective optimization (MOO)Wireless sensor network (WSN)

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Wireless Sensor Networks (WSNs) are crucial for Internet of Things (IoT) data transmission.
  • Efficiently managing heterogeneous devices in IoT networks presents a significant challenge.
  • Existing solutions leave a research gap in optimizing IoT network performance.

Purpose of the Study:

  • To address the challenge of efficient device utilization in heterogeneous IoT networks.
  • To propose and evaluate an efficient model for improving IoT network performance.
  • To bridge the existing research gap in IoT network optimization.

Main Methods:

  • Development of a novel efficient model tailored for IoT environments.
  • Testing the proposed model against 25 established IoT benchmark problems.
  • Comparative analysis of the model's performance against existing solutions.

Main Results:

  • The proposed model demonstrated superior performance in addressing IoT benchmark problems.
  • Significant improvements in efficiency were observed across various IoT network scenarios.
  • The model effectively handles the complexities of heterogeneous IoT devices.

Conclusions:

  • The developed model offers a promising and efficient solution for current IoT network challenges.
  • This research contributes to optimizing data transmission and device management in WSNs.
  • Further research can explore the scalability and adaptability of this model in diverse IoT applications.